TBPN Live - AI Is Coming for Your Memes, Axios NPM Package Compromised, Claude Code Source Code Leak | Alex Pruden, Qasar Younis, Sebastian Mallaby, Forrest Heath, Dino Mavrookas, Will Ahmed, Jannick Malling, Ryan Daniels, Chris Yu

Starting point is 00:00:00 You're watching TVPN. Today is Tuesday, March 31st, end of Q1, 2026. Boy, we're live for the TVPN Ultradome, the Temple of Technology, the Fortress of Finance, the Capital of Capital. Let me tell you about ramp.com. Time is money, save both, easy to use, corporate cards, bill pay, accounting, and a whole lot more, all in one place.

Starting point is 00:00:19 Yay! I got a new sound cue. I know. You were pulling for me? Dangerous. I got three now. Dangerous. I got three now.

Starting point is 00:00:26 Watch out. I'm not going to go too crazy. I'm not going to overdo it. We've been there. We learned. We changed, we evolved, we became better as people. As did our linear lineup, we have a banger show. Let's pull it up.

Starting point is 00:00:37 Linear, of course, is the system for modern software development. 70% of enterprise workspaces on linear using agents. Alex Pruden. Yes. We're going to be talking about Google's quantum news. The crypto quantum crash. Say that three times fast. Crypto quantum crash.

Starting point is 00:00:54 Then we have Kayser from applied intuition. Yes. Very excited to catch up with him, an absolute dog. Then we have Sebastian Malibi, releasing his new book, The Infinity Machine, an insider account of deep mind. Tyler's got it pulled up right there. Super Intelligence. I'm a huge fan of Sebastian Malibai. You might have read more money than God.

Starting point is 00:01:13 You might have read the power law, the history of Silicon Valley. It's the definitive count of how venture capital became what it is today. Highly recommend that book. This is a very interesting departure from that because it focuses on a single person, it's a biography, not a history of an entire industry. but very excited to talk to Sebastian Alibi. And then we have Forrest from Somos, raising a $40 million round. Then Dino from Seronic, Will from Whoop, Janick from Public, Ryan from Crosby, and Chris U.

Starting point is 00:01:42 He's working on a spin-out from Rivian. Very exciting. Already has a billion-dollar valuation. There we go. Well, a friend of the show, our president here at TBPN, Dylan Aberskato, headed to the TBPN newsletter, which you can sign up for at TBPN.com. wrote a fantastic essay, summarizing a trend

Starting point is 00:02:03 that we've been discussing with him around how AI is changing meme making. And I found it very interesting. I'm glad that he wrote this piece. And so we'll read through this and then discuss it, debate it, and see where we can take it further. And then obviously. And Dylan's from Long Island, New York.

Starting point is 00:02:20 So John is gonna be trying to do it in a Dylan Amberscato impression. Kind of accent. Memes are changing. That became abundantly clear during the Oscars a few weeks ago. When Conan tried to create a new Leonardo, Leonardo DiCaprio memes, I don't know what accent that was.

Starting point is 00:02:37 That's just like UFC announcer to go alongside the classic Leo memes. In doing so, especially by using TFW, that feeling when, and the blocky white font that defined early internet memes, he inadvertently demonstrated that the meme templates millennials grew up with have become increasingly stale, even cringe. That's a good point. Instead, AI-generated videos are the new meme template that every network and studio should be focusing their launches on. Look at what happened.

Starting point is 00:03:07 Look at what's happening with the Harry Potter reboot. When the trailer first dropped, the reaction to the new Snape played by Ghanian. Ghanian. He's from Ghana. Ganean. English actor, Papa Isidu, was predictably and unfortunately negative. According to the L.A. Times, he received death threats since being cast in the new role. But after a few incredibly viral and well-produced AI videos, one, an original Snape versus Black Snape MMA match and another AI-generated rap video and another Dripworts, the school of Drip, the narrative has started to shift. Have you seen any of these? I think I've seen drip warts, but can we pull up the original, the quote-unquote original Snape versus Black Snape M&MMA match? Because I have not seen this one. And I think it is illustrative of what to be.

Starting point is 00:03:58 Dylan is talking about here. Snape v. Snape in the UFC ring. While we pull that up, let me tell you about Plaid. Plaid powers the apps you use to spend, say, borrow, and invest, securely connecting bank accounts to move money, fight fraud, and improve lending now with AI. And let me also tell you about Restream, one live stream, 30 plus destinations. If you want to multi-stream, go to Restream.com. So let's take a look at Snape v. Snape in the UFC ring. Any luck? Here we go. I just dropped it in. Cool. And we have a few others here. The videos have amassed tens of millions of views, and on Dylan's timeline, at least, sentiment around both the character and the reboot has been a complete 180.

Starting point is 00:04:35 Here we go. Really photorealistic. Is this, are there any red flags here as a UFC enjoy, or does this feel like a proper UFC? I'm in the actual video quality is insane. Wait, but old Snape won. In the fight? Yeah. Okay.

Starting point is 00:05:02 But I think it just... Okay, wait, how do you know that? I think it just sort of like makes the characters more entertaining, more fun, shows you that this is just creativity at the end of the day. This is just, like, you should not be so up in arms about something that's a movie.

Starting point is 00:05:22 Like, it's entertainment, and here's some more entertainment. And so you're adding entertainment to the discussion, and people are enjoying that. There's another AI generated rap video about the new Snape, which we can pull up a little bit of here. AI meme videos are inherently viral and driving real awareness in a way traditional memes no longer can, not just because they're novel and more entertaining, but because a single AI clip can travel further and compound harder than traditional meme formats and social feeds that now heavily favor video. This suggests, yeah, that's interesting.

Starting point is 00:05:54 On X, it's still very easy for an image to go viral, but if you think about Instagram, YouTube, like a standalone image just can no longer actually get that escape velocity. I mean, what about dripped out Pope? Remember that? Yeah, a little bit, but people are just spending so much time in the short form feeds. And there can go in there, but there's certainly... Yeah. Yeah, I mean, I guess even some of the dripped out Pope or what was it, is it Valenciaga Pope?

Starting point is 00:06:25 I don't remember what the name was, but Dylan... That Pope says, this suggests a new playbook for Mark. especially in entertainment. If you're about to drop a trailer for a new movie or show, you need to be thinking about your rage bait character, the one people will latch onto, remix with AI and build around. Conan tried to force a Leo meme down our throats at the Oscars. Didn't see that because I was sleeping,

Starting point is 00:06:48 but this might have worked 12 years ago. That playbook is over. Today in rage fans and communities will, if you're successful, take your characters or moments and turn them into something much bigger, entire cinematic universes. Yeah. I'm just very impressed by the overall quality of those outputs. The Oscar selfie, I remember this. This, I think, became the most liked image on Twitter at the time in 2014, briefly.

Starting point is 00:07:13 That image, this is the canonical clout bomb. If you're a fan of Bradley Cooper, you like it. If you're a fan of Merrill Streep, you like it. You're a fan of Brad Pitt, you like it. And so you're amplifying all of the ultimate collab post. And this has become a format that's been used. time and time again. It's effective. We did a little bit of it at the Super Bowl. It's fun. It works. But now the future is AI. Let's pull up the DripWort School of Drip video. I want to watch this one.

Starting point is 00:07:44 Because I saw a clip of this. I didn't see the whole thing. Let's see if we can play this. That's Harry Potter. Are you really Harry Potter, my G? Type shit, type shit. Type shit. None of that. None of that, broskey. We're all here on the Mayback Express for one reason, and one reason only, and that's to go to Dripwatch, the school of Drip. The Maybach pulling the trade is pretty good. Hey, time of, tell my my bad, I'm going to check the side. Y'all, y'all.

Starting point is 00:08:17 And there's the new Snape character. So, yes, very effective. I was reflecting on this and thinking about how it's not just AI videos that are unlocked as the new meme format. Like, 20 years ago, video editing was extremely difficult. Like, you had to do it on a desktop. You had to have a piece of software that probably cost a lot of money. It was not widely accessible. And so these image makers, image memes, we were, I was talking to Brandon about this,

Starting point is 00:08:48 like, good guy Greg was one of these, or like the insanity wolf. And it would just be like a picture, one image of a duck. And the duck would be on sort of like a solid, colored background. And that would be the template. And then somebody would put white text with black, like block text, impact font on the top and the bottom. And that was like the image meme. And that was accessible in the sense that it could be like generated on MS paint. It was, it was free to generate it, basically. Then we got video editing, you know, Capcut, Instagram Reels as an editor called Edits. And all of a sudden it became easy for someone to take a vibe reel and put

Starting point is 00:09:28 different text over it, I send you a bunch of these where I'll find some crazy vibriel and I'll just re-contextualize it with a new, yeah, you know, laughing thing, new caption, basically. And so the classic one is like those four, those four jets and the new top gun. And it's like, when you and the boys all drive somewhere in separate cars or something like that, you know, as an example. But now you can generate, you know, full AI videos that can express the joke of the meme. And I think the next version of this is like software, as a meme, S-A-A-M, something like that. And we've been experimenting that with the simulators.

Starting point is 00:10:04 There's TBPN simulator, Jeremy Gaffan simulator. There are more simulators coming. And all of a sudden, we, you know, the idea of building a video game, becoming a video game studio was like an impossible challenge. It would be months and months of time, maybe millions of dollars to get anything reasonable. So you had to be commercial about it.

Starting point is 00:10:24 You could not do it as a comedy bit. But now you can, or, or if you can, Or it's getting closer. Certainly, our organization is set up to where we can turn Ben or Tyler loose for a few weeks and say, yeah, like, you know, work on this vibe coding project for a few days, a few weeks. Like, it's okay. You don't have a lot of other responsibilities that are going to creep in. But increasingly, it's going to be more and more just like a few prompts on your phone to get the piece of software that is that meme. And you can think about the J-Mail suite from Riley Walls as another software.

Starting point is 00:10:58 as a meme moment where he's making a commentary on the Jeffrey Epstein saga and all of that, but he's instantiating the humor, the commentary in a piece of software that actually works. Although, of course, the feature set is a little bit boiled down from the full Google suite, but the UI is familiar and the UI is part of the joke. And so I think that's a little bit of where this goes. Well, let me tell you about cognition. They're the makers of Devin, the AI software engineer, crush your backlog with your personal AI engineering team.

Starting point is 00:11:32 And let me tell you about label box. Oops, sorry. Label box. RL environments, voice, robotics, evals, and expert human data. Label box is the data factory behind the world's leading AI teams. So there is a whole bunch of hack news going on. We're in a very weird week in terms of the news cycle because it's spring break. And so a lot of executives of big tag companies are like,

Starting point is 00:11:54 don't launch while my kids are out of school. and we're going on vacation. I actually think this is my real theory. So we're in a little bit of a slow news week, and you can see that, like, the journal is covering announcements that happened last week. They're talking about SORA. They're talking about Disney.

Starting point is 00:12:09 They're talking about, you know, things that are more, like, reflective in Stratectary. Ben Thompson has sort of a 50-year retrospective on Apple. It's not driven by a news item. Like, it's not like Apple launched a new product this week. So Ben Thompson is taking a step back and reflecting, it's a great piece. But it's not exactly news driven because there isn't that much news coming from big tech companies coming from the labs, etc

Starting point is 00:12:32 But there are a ton of crazy hacks starting with Axios There's an active supply chain attack on Axios one of NPM's most dependent on packages So if you have been vibe coding Axios is a is a package that helps with HTTP requests so it gets sucked into all sorts of different projects and if you upgrade it to the latest version you basically got a virus with that. And if that's running in the cloud, it's building, and that's probably maybe bad because it could steal API keys or SSH keys. It could do a lot of things. It could wreak havoc on your system. Also, if you built this piece of software and you included the contaminated Axios installer or package locally, it could potentially weasel its way out of your local

Starting point is 00:13:23 environment and get onto your desktop. It's a virus. So be careful out there. And I'm sure people will be responding. The recommendation from Ferros, who sort of broke the news over at socket security, is that if you use Axios, pin your version immediately and audit your lock files, do not upgrade. Socket analysis confirmed that this was malware. Plain CryptoJS is an obfuscated dropper loader that de-obuscates embedded payloads and operational strings at runtime dynamically loads FSOS and exec sync to evade static analysis, executes decoded shell shell commands, stages and copies payload files into OS temp and Windows program data directories deletes and renames artifacts post-execution to destroy forensic evidence. So very risky. I would say like if

Starting point is 00:14:15 you have installed this, you should just like freak out basically. Should and and And if you break your computer, that's like the first thing you should do. Just like try to slam it over your- Yeah, take the computer, throw it in the lake. Throw it in the ocean. That's how you should start. I concur. I mean, practical, yeah.

Starting point is 00:14:34 I mean, there is going to be some sort of like power law response here where of the people that are victims of the attack, they will go after the most vulnerable with the highest, like, ransomware potential. And I think we're seeing that with one company, I believe Mercor was targeted. but I don't believe, was that, my understanding is that, the crazy thing is you have,

Starting point is 00:14:56 you have this, like, Claude Code leak. That was completely separate. Even though, even though I do believe they use Axios in Claude Co. Okay. So something on that. Sure, sure, sure.

Starting point is 00:15:06 And you have the Mercor leak, which is, it's a ransom. It's a ransomware. Someone stole some data. Yeah, they stole a bunch of data and now they're trying to, you know, get bids on it. We'll get to that in a little bit.

Starting point is 00:15:19 Okay. And then there's this Axios supply chain attack. A niche had a little bit more context. He said a tiny piece of code called Axios runs inside almost every app on your phone and every website you visit. Developers download it 100 million times a week. A few hours ago, someone poisoned it with malware that hands an attacker full control of your computer. If you've never heard of Axios, that's normal. It does one boring but important job.

Starting point is 00:15:42 It lets apps talk to the internet. When a website pulls up your feed or an online checkout processes your card, Axios is probably doing the work underneath, over 173,000 other code packages plug into it. It's everywhere. The attacker stole a lead developer's login for NPM. Think of it as an app store, but for code that programmers use. Once inside, they swapped the developer's email to an autonomous proton mail account and uploaded the poisoned version by hand.

Starting point is 00:16:07 That jump past every security check the project normally runs before new code goes live. And this was not a rest job. The stackers staged the malware at least 18 hours before pulling the trigger. They built separate versions for Windows, Mac, and Linux. They poisoned both the current version and an older one within 39 minutes of each other, casting the widest net possible. Once the malware ran on a machine, it deleted itself to cover its tracks. The trick was smart.

Starting point is 00:16:31 They never touched a single line of code inside Axios itself. Instead, they tucked in a fake add-on called Plain Cryptojs, built to pass as a well-known trusted library. It copied the real library's description and author info, so nothing looked off at a glance. When a developer installed Axios, this fake package quietly ran the malware on its own. When a smaller package called UA Parcer.js got hijacked back in 2021 with about 8 million weekly downloads, the security world treated it like a four alarm fire. Axios has 100 million over 12 Axi exposure with 173,000 packages depending on it.

Starting point is 00:17:06 Socket, the security firm that flagged this caught it in about six minutes. That's fast, but six minutes is still plenty of time for automated systems. At companies everywhere to pull and install the bad version before anyone can react. If you or your team run Axios, freak TF out. Now, lock your version to 1.14.0. Change every password API key and access token on any machine that installed the compromised update. And check your network logs for connections to sFRCLAC.com or the IP address, 14211, 20673. Carpathie had some context if you want to go through this, John.

Starting point is 00:17:46 I will, but first I'll tell everyone a very important message from CrowdStrike, which is super relevant today. Your business is AI, their business is securing it. CrowdStrike secures AI and stops breaches. And I'll also tell everyone about Cisco. Critical infrastructure for the AI era. Unlocked seamless real-time experiences and new value with Cisco. So, Andre Carpathie said, new supply chain attack this time for NPM Axios. The most popular HTTP client library with 300 million weekly downloads. that's a lot.

Starting point is 00:18:17 Scanning my system, Andre Carpathie says he found a use imported from Google Workspace slash CLI from a few days ago when I was experimenting with Gmail G-Cal C-LI. The installed version luckily resolved to the previous version, the unaffected 1.13.5, but the project dependency is not pinned, meaning that if he did this earlier today, the code would have resolved, everything would have updated,

Starting point is 00:18:45 and he would have been poned. It is possible to personally defend against these to some extent with local settings, e.g. release age constraints or containers or etc. But I think ultimately the defaults of package management projects, PIP, NPM, etc., have to change so that a single injection, usually luckily, fairly temporary in nature due to security scanning, does not spread through users at random and at scale via unpinned dependencies. So very, very crazy, crazy story. Scott Wu said that Devin Review caught the Axios supply chain attack for multiple cognition

Starting point is 00:19:25 customers before the attack was publicly known. These attacks will be 10x more frequent in the age of AI. It is critical that repo maintainers start using AI for defense as well, showing one example below where Devin Review caught the attack within an hour of its release, text minorly edited for anonymization. So I was debating this with Tyler earlier. The question is like, how does this update diffusion of coding agents, diffusion of vibe coding.

Starting point is 00:19:55 I was sort of saying, is this bullish for cursor, windsurf, you know, code readers? Because you would see an organization that said, hey, we were having a great time vibe coding. But going forward, we have a standard in this organization that we're going to have more more humans in the loop? Does this make people be more inclined to put humans deeper into the situation? Tyler's counterpoint, I'll let you explain how you were saying that maybe this is actually bullish for just more token generation, more code gen. Yeah, I mean, clearly like there just needs to be more code review, right? Okay. The package was still seen within seven minutes by an automated system, right? That's true. So like, yeah, I think people will just like, there's going to be much more of an emphasis,

Starting point is 00:20:42 like, okay, you use a coding agent to write the code. You also use a coding agent to review the code every time. Like right now, that's kind of a thing you do maybe later. If you're in a big team, you have code review, but if you're just doing it solo, maybe you don't do as much code review, right? Yeah. But it just becomes more embedded within the agents, right? You talk to codex, you talk to cloud code.

Starting point is 00:20:59 Yeah. There's already like every single. I just think it's bullish overall for cybersecurity. Like, I think every cybersecurity company will probably do well. People are on edge already. Yep. and even though this type of attack has happened for years long before, like the popularity of vibe coding, it just feels like there's a bunch of new solutions that are needed.

Starting point is 00:21:21 The kind of incumbent cybersecurity players will do well. They're going to release a lot of new products. I think the question that I have is like, why seven minutes, right? Yeah. Why not check it before it's merged in in the first place? Yeah, yeah. Or just like, you know, these are machines. so theoretically they can be constantly monitoring versus like.

Starting point is 00:21:44 Yeah, I don't know. And the question is we're going to be digging into this story more over the next few days. But I'm interested to know, like, it's found in seven minutes. When is it actually rolled back? If you look at 300 million weekly downloads, like clearly there are people that were downloading it at that moment in time. At all seven of those minutes, there's probably like thousands of downloads, if not, you know, 10. of thousands, just doing like a rough ballpark on what seven minutes means over a week of 300 million per week.

Starting point is 00:22:15 But the question is, like, how quickly was it rolled back? So is it only if you're in that seven minutes, or was it discovered in seven minutes? And then it took them another 20 minutes to roll it back and stop serving the contaminated package. Understanding the scope of this, because it's very clear that, as Andre Carpathie explained, like he was actively using it every single day and yet was not caught in that. seven minute window and so he was cleaned and and understanding the scope and scale of the impact is very much determined by how many um just just how just just how broad and how many installs

Starting point is 00:22:53 happened during the contamination anyway will brown has a good take he says i hope someone axios is reporting on this and i completely agree it's going to be it's going to be confusing when they do anyway let me tell you about gusto the unified platform for payroll benefits and hr built to evolve with with modern, small, and medium-sized businesses. And let me also tell you about 11 labs. Build intelligent real-time conversational agents. Reimagined human technology interaction with 11 labs. So, moving on.

Starting point is 00:23:19 Last night. More leaks. What's going on? Last night, quad code, source code, was leaked. Via map file in the NPM registry. There's just a link to. Wait, someone just actually, do not click a link.

Starting point is 00:23:34 If somebody ever says, hey, I got some really great source code here. Just click this link. probably don't click it, let other people screenshot it. There's plenty of meta-analysis over here. Seems messy, seems unfortunate. Heart goes out to the folks who are dealing with the situation. At the same time, Codex is open source.

Starting point is 00:23:54 It's not the end of the world. But it did reveal a bunch of things about the roadmap and also some of the internal April Fools. That is the worst part. We love a secret surprise April Fool's joke. I love a good joke. and nothing spoils a joke like hearing about it a day early. But much more importantly, there are lots of other critiques of the way Claude

Starting point is 00:24:17 is implemented. What are the bad words? Yeah, I don't think this hurts their business at all. No. Because people are using Cloud Code to make other products. Yeah. And then also having to take basically a fork of Claude code, maintain that, try to be shipping features against it, which is, again, I think it's, it's, it's, it's, it's, it's,

Starting point is 00:24:37 It seems to not be legal at all to just fork the code base just because it's out there. Oh, yeah. You can't just like steal this of your business. People are converting it into other languages and maybe there's some argument there. But still, I don't think this hurts their business at all. Understand some of the secrets. What's special? But at the end of the day, all of these tools, especially something in ClodCode that's so new,

Starting point is 00:24:59 like it's more of like the process. It's more bad for the overall brand of vibe coding. Totally. Totally. Totally. Yeah. Yeah, it's rough. And it's, and the, you know, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, uh, the, uh, the, the, uh, it's all the big cyber companies have been selling off, you know, tens of billions of dollars. Yeah, yeah, yeah. The question of like, yeah, yeah, does this build trust in, like, using via code? Yeah. So, overall, overall, it, uh, it, uh, it, it, uh, it, uh, it, uh, it, it, uh, but again, you know, very obviously going to get through this. Yeah, so the how it started, how it's going is, of course, landing like a ton of bricks. In the last 30 days, 100% of the contributions to Claude Code were written by Claude Code.

Starting point is 00:25:45 And how it's going is that it leaked the source code, which is not what you want to have happen. Yes, Angel says Mythos is so good at security that Claude Code, source code got leaked. Okay, let's, I don't know, should I, this is like, you know, you didn't get to watch the Super Bowl. You have it DVR'd at home. Do you want spoilers? Should we review the April Fool's joke or should we leave it unspoiled so that we can enjoy it tomorrow? What do you think? I mean, it's not, it's not, it's cool.

Starting point is 00:26:18 It's very cool. You've already read it? I read through it. But it's not, it's not to my, I don't think we're getting, I don't think we're getting a knee slapper out of it. Okay. It's very cool. Okay. I think it'll be cute.

Starting point is 00:26:29 Okay. Well, well, then we can move on. What else, what else do we learn? Tuki summed it up here. Do you understand what just happened to Anthropics? Someone on their team ran a production build of ClaudeCode code. The compiler generated a dot map file, which is literally a blueprint that reverses the entire code base back to its original source. And then they published it straight to NPM for the whole world to download.

Starting point is 00:26:53 And it really does show you how fast the NPM downloads. Like, there are people that are downloading it every single minute. And so even if it's only up there for a minute, someone's going to get it. And then all they need to do is send it to somebody, zip it and post a link on X and it goes viral. It's like locking every door in your house, installing cameras, hiring armed guards, then accidentally uploading your floor plans to Google Maps. Does that matter? No, that's a bad analogy.

Starting point is 00:27:16 I don't like that analogy. Because floor plans are not why I lock every door in my house. I install cameras. I hire armed guards. Aren't floor plans public on like Zillow? Oftentimes. I would say we can probably skip over this. John, if you scroll down this account, just come.

Starting point is 00:27:32 kind of posts like the same format every single time. So we can skip that. Let's go over to Lisan. If there's a red alert emoji, you got my attention. Let's go over to Lisan Algae. Yes, yes, yes. A few takeaways from the Claudecotech. Anthropic is actively using mythos for development.

Starting point is 00:27:47 Okay. They are already a Capi Bar, a V8. We learned last week that Capi Baras are extremely deadly, but can be deadly in the right context. Capy Bar is crazy. The foreshadow is crazy. The foreshadow is crazy. We were talking about how the Faustian bargain that is getting up a Capibara as a pet.

Starting point is 00:28:07 It seems so cute, but it can bite you. And it seems like that might be what happened. Capybar has $1 million token. Context Window and Fast mode. Cool. Numbat is another interesting code name tagged with at model launch. Remove this section when we launched Numbat. Fenwick seems to be the Fennick Fox.

Starting point is 00:28:26 Fenne Fox is very cute, but also not a domesticated animal. How about we get some golden retriever code names? How about big fluffy poodle? That's a good code name for your, for your animal-themed AI model. Anyway, let me tell you about console. Console builds AI agents that automate 70% of IT, HR, and finance support, giving employees instant resolution for access requests and password resets. And let me also tell you about Lambda.

Starting point is 00:28:53 Lambda is the superintelligence cloud, building AI supercomputers for training and inferences scale from one GPU to hundreds of thousands. Arvid says hot take, anthropic leaked clod code in 10. Eventually, to get a Nerdosphere code review, it would have never gotten if they had just open sourced it. Oh, that's actually true. Way more attention. You don't leak your entire feature roadmap and you don't do, I mean, it's funny, and I'm sure they'll make the most of this. This is 4D chess right here. But I'm not seeing the 4D chess.

Starting point is 00:29:22 I'm seeing the 40 trust now. I'm convinced. This is, I mean, we're in completely uncharted territory for marketing stunts and pre-releases and sneaky footage that is goes viral and maybe was planted and you don't know and it's like some leaked account like I don't know I think everything's I think the gloves are off everything's on the table this could be an April Fool's joke this could be a stunt to draw to drive attention to an open source move although Tyler you said that Dario is not a fan of open source at all right he's like against unilaterally he doesn't want to do open source I I feel like isn't there some steel man there where where

Starting point is 00:30:02 If you open source, like, I don't know, like, opus two or something that's like really old, it's entirely commoditized in the research community. So all of those secrets that went into like making Opus II good, those have been commoditized. They've been discussed at the house parties in SF. The researchers have moved from one place to another. So everyone knows these that have implemented. They're available as open source. But by open sourcing your model, you can.

Starting point is 00:30:32 share with more of like the up and coming academic community. Like if I'm a computer scientist, I'm interested in the research is already commoditized. Yeah, I guess you could just use the other ones. It doesn't really have a benefit. Maybe. Yeah. So has anyone at anthropic, has anyone enthropic commented on this at all? I haven't seen anything.

Starting point is 00:30:51 I haven't seen anyone. Yeah. What is undercover mode? That is a way to contribute to projects without letting people know that you're using. Claude code. Oh, interesting. That's a hack. Gergley over at Pragmatic Engineer says this,

Starting point is 00:31:11 Gergi, sorry. This is either brilliant or scary. Anthropic accidentally leaked the source code of Claude Code, which is closed source. Repos sharing the source are taken down with DMCA, but this repo rewrote the code using Python, and so it violates no copyright and cannot be taken down. Okay, and there's a warning.

Starting point is 00:31:30 Do not store the code, even though it has leaked. Do not store it because you might get DMCA'd, according to the Primigen. The last time Anthropic, in their infinite Ph.D. level wisdom, leaked their own source code. February 25th, that happened? I missed that entirely. They DMCAed all repos that had their code. Careful storing the code because Anthropic will have no mercy. 40,000 users forked it, so maybe unfork it if you did that because it sounds like you might

Starting point is 00:32:00 might get a legal letter. Again, a DMCA is not, is not like an actual lawsuit. It's more just, on fork, on fork. And people of course making a joke that the Codex source code has been leaked in full here. And they're linking to the GitHub because Codex is open source, which is cool. I don't know. It's interesting. And more and more people are building their own harnesses. There are some interesting data that Opus performs extremely well, better than in clog code in cursor on some benchmarks. And so there is this new, this new paradigm of like, you know, how can you add different value when you're building a harness?

Starting point is 00:32:38 So what else? Yeah, certainly there's other, plenty of other companies that are building harnesses that they're going to be able to dig through this and get some benefit, be able to improve their products. That's not great. But at the same time, Codex has already, the source code is already open source. Yeah. And so that's not, that hasn't been hurting code.

Starting point is 00:32:58 is progress and growth. So end of the day. Ultimately, I would say, I'm assuming very, very embarrassing for the individual that ultimately contributed to this, but they will get past it. Well, we will put the blame squarely on the AI model so they can take it. Dax is getting line of code mogged, LOC, mugged, because clog code open source is, plug code source is 512 lines of code

Starting point is 00:33:30 whereas open code his project is only 118 lines and so he's got to get those numbers up and GT mogs everyone with over 50 billion lines of code he doesn't have 50 billion lines of code GT Gary Tan will be coming on the show hopefully this week and we will get the full

Starting point is 00:33:44 scoop on how he's using GSTAC and other models which should be fun before we move on let me tell you about turbo puffer serverless vector and full tech search built from first principles and object storage fast 10x cheaper and extremely scalable and let me also tell you about vibe.co

Starting point is 00:33:59 Where DDC brands, B2B startups, and AI companies, pick channels, advertise on streaming TV, pick channels, target audiences, and measure sales, just like on meta. Zach says, NDAs are a great way to keep your corporate secrets safe from one or two beers,

Starting point is 00:34:11 but not three beers. Why is there a community note on this? Oh, this joke was posted before on Instagram. It's a little joke theft. Interesting. Got it. But it's a good joke, and I'm glad that he brought it over to X

Starting point is 00:34:25 where we could enjoy it. along with 36. The original post was an NDA is a lock and three beers is a key. Okay. Well, yeah, he toned it down for the timeline. Anyway, there is news out of Google. A Google paper warns that warns crypto on quantum risk ahead of 20209 timeline. So we've heard about the risk of quantum computing affecting the cryptocurrency industry,

Starting point is 00:34:54 crypto projects broadly. there is some new research out of Google that provides some more perspective. So Google researchers have warned that future quantum computers may be able to break some of the cryptography protecting Bitcoin and other digital assets with fewer resources than previously thought, adding urgency to the debate over how the industry should prepare. The researchers did not indicate such a machine exists today, but said new work suggests the computing power needed to carry out that kind of attack, maybe lower than the machine. than earlier estimates had suggested.

Starting point is 00:35:27 In a Google research blog post, this is from Bloomberg, the researcher said that a future quantum computer could break elliptic curve cryptography, a form of public key encryption used across much of the market. Their latest estimate points to a 20-fold reduction in the quantum computing hardware needed to break what's known as ECDLP 256, a mathematical problem that helps secure crypto wallets in transactions.

Starting point is 00:35:52 That does not mean Bitcoin and Ethereum are suddenly exposed, But the researchers in the white paper dated Monday said the clearest defense is a shift towards post-quantum cryptography or PQC. I'm sure this will be a hot topic over the next few months. A newer form of security designed to withstand attacks from powerful machines. They also urge the crypto industry to cut avoidable risks in the meantime. We urge all vulnerable cryptocurrency communities to join the migration to PQC without delay. Google cast the paper as a warning meant to give the industry time to, time to,

Starting point is 00:36:25 act not as a prediction of imminent collapse. Last week, the tech giant introduced a timeline to fully migrate its own security systems to post quantum cryptography by 2029. Fears around quantum computing is a realistic threat to crypto have swirled for years. In January, Coinbase established an independent advisory board to study what quantum computing could mean for the blockchain. That's the month. Christopher Wood, global head of equity strategy at Jeffries, removed a 10% allocation to Bitcoin from his model portfolio, citing fears that the advent of quantum computing could undermine the token. On Tuesday, Bitcoin shrugged off the news of the Google paper, making the rounds, rising

Starting point is 00:37:04 as much as 2.6% to $68,300. I'm not sure where it is today, but a majority, I'm sure you can pull that up. Even so, the researchers said the time left before such machines arrive still appears longer than the time needed to move public blockchains to post-quantum cryptography. However, BTC is currently at 67. 67. So slightly off of yesterday. A lot of this stuff has been discussed ad nauseum in the crypto community for years. I remember hearing about quantum potentially breaking Bitcoin as far back as 2016. So you're saying you were already in that kind of like post-quantam? Yes, 100%. I was locked in. No.

Starting point is 00:37:45 I was aware of it. One concern that people in the community have had that I've seen talked about is this idea that if you did have a computer powerful enough to crack these encryptions, you would, unless you were like Google and you already had, you know, billions and billions and billions of dollars of cash flow, you wouldn't exactly stand up and say like, hey, I have cracked Bitcoin because the incentive for a certain team would just be to go around and find these wallets that were maybe, maybe didn't have any activity for a long time and just start cracking those individually. Because if you just stood up and said, hey, I have a quantum computer that destroys Bitcoin. The price would go down and then the hacker wouldn't get any benefit from it.

Starting point is 00:38:37 Yeah. It's interesting. What are quantum stocks doing on this news? probably ripping they rip on everything Cy quantum is that one of them Riggette's up 8% Okay there we go Oh sci quantum's probably

Starting point is 00:38:54 privately held There's another one Dwave right D wave are they public Yeah they're up 10% today But they're down 12% over the past five days But and 25% of the last month

Starting point is 00:39:06 and 42% over the last six months But they're up 88% over the past year, let's go. D-Wave is a $5 billion company. Yeah, there's apparently a bull market and Nick on our team's email inbox. Oh, yeah? Quantum companies. Really? Right now?

Starting point is 00:39:21 Okay. Talk about. Well, we do have someone coming on, right? We have Alex Prudent from Project 11 coming on to break it down for us at noon. So Nick Carter was talking about this. He said, many are wondering what Google saw that caused them to revise their post-quantum cryptography transition deadline to 2029 this week. It was this, and it's from research, Google, research doc Google, which we will go through.

Starting point is 00:39:46 Max the VC says, Google's basically saying, we've cut the quantum resources needed to break Bitcoin's encryption by 20x. We can now break it. We can prove it. We're just not going to tell you how. We've slowed down research to give crypto a chance. You have until 2029 to figure out a solution. Good luck.

Starting point is 00:40:04 Elon chimed in and said, on the plus side, if you forgot your password, the password to your wallet, it will be accessible in the future. Also to everyone else. Yeah. Yeah, I don't know. I mean, how do property rights? If somebody does have a quantum computer and they crack your Bitcoin wallet

Starting point is 00:40:24 that you forgot the password to, but you can prove that you owned and then they get busted for stealing your Bitcoin, you could potentially get it back. Do you ever really own code? I don't know. Nick also said, and the craziest thing is that the quantum AI,

Starting point is 00:40:39 Google Quantum AI paper is maybe not even the most concerning quantum paper release today from Project 11, who's coming on. Shores algorithm is possible with as few as 10,000 reconfigurable atomic qubits. So this will be interesting to dig into further. Within minutes, with 500,000 physical qubits, Google is now more confident on a 2029 post-quantum transition. Well, speaking of Google, Let me tell you about Gemini 3.1 Pro. With a more capable baseline, it's great for super complex tasks like visualizing difficult concepts, synthesizing data into a single view

Starting point is 00:41:17 or bringing creative projects to life. And let me also tell you about graphite. Code review for the age of AI. More important than ever. Graphite helps teams on GitHub, ship higher quality software faster. So, there's a lot of news about this quantum story. Nick said, good morning.

Starting point is 00:41:35 Now is not the time to panic. The time to panic is if Bitcoin devs, read these two papers and double down on their chosen solution of hoping it goes away. Then panic. That's ridiculous. Dan Shipper says, the first thing I've seen that could make Bitcoin go to zero or allow competitive coins to catch up. So other coins clearly have at least like a very clear like marketing story to tell if they

Starting point is 00:42:02 are like the quantum proof or the first to be quantum proof or the most seriously regarded in the quantum proofing race. will be interesting. Ariana Simpson chimed in and said, except all or most other coins have this problem too. But that is the opportunity that someone can maybe change something. So the chance that NASA lands on the moon,

Starting point is 00:42:21 we were tracking this yesterday. The missions are starting to happen. Before 2028 on Kalshi is now at 14%. Before 2027 is at 4.7%. So they are racing. Of course, this Artemis 2 mission is not boots on the ground on the moon. It is rocketing around the moon.

Starting point is 00:42:42 We'll have more about this tomorrow. They're just going to check it out. They're going to be gone for 10 days. They're going to be in space for 10 days. And we'll be very interesting. Brandon Grell was doing some deep dives on the technology, the streaming technology, what we really care about here,

Starting point is 00:42:59 that will be on board. Something like 20 cameras, 4K live streams, laser beams to make sure it's low latency. Super chats. It should be a lot of fun. Super chats. would be good. We got to get a chat going. I'm sure there might actually be, because they usually stream on YouTube, and so I wouldn't be surprised if there is. Is it going to be a 24-7, like,

Starting point is 00:43:19 perpetual stream that's always on? Yeah. Even when the astronauts are taking a sleep. Yeah. Taking a little nap. Yeah. Yeah. Okay. Yeah. Okay. Yeah, it's going to be funny. VFX artists are going to be working there watching it very closely and then pausing. There was a glitch. Did you see that glitch? That was, that was VFX. That was AI. No, this is my mark. I will believe that it's real if I see an astronaut put three fingers in front of their face. Yep. Because this is the one thing that the AI can't do right now.

Starting point is 00:43:49 If you're ever on a Zoom call with someone, you suspect of being fake, a scammer who said, hey, let's get on Zoom. Let's talk about some financial investment opportunity. And it looks like someone you think is the person, but you suspect that it might not be. and they will be able to show you, look at the fingers. The fingers are perfect. It's fine. That's because this part is not AI.

Starting point is 00:44:16 Just the face is AI. This is the deep fake stuff that's happening. So what you have to do is you have to ask them to hold up three fingers. They'll be like, yeah, three fingers. This is fine, right? I satisfy the task. You got to say, no. Put the three fingers in front of your face.

Starting point is 00:44:28 Because if you put the three fingers in front of your face, the AI gets confused and it breaks the deep fake that's happening underneath. So you got to go like this. There you go to go. You had three fingers in front of the face. This is the trick. This is the only way you'll survive in the future. Be careful out there.

Starting point is 00:44:44 Mercor had a breach. This is crazy. The design language for the hacker is very hacker-coded. The hackers that are putting out a bounty created like an image that looks very aesthetic to me. The design of this. I didn't realize hackers. did stuff like this. This is very interesting.

Starting point is 00:45:10 But, you know, it's like, you think about the hackers. They're kind of like cosplaying as hackers. They are. But they have. They've like adopted like the green, like the green text in the black terminal. It's like they're, they're living the, they, it's, it's like life imitates art. That type of thing. Anyway, it seems like a very rough leak, very unclear what's actually happening.

Starting point is 00:45:32 There's a whole bunch of different questions in here. There's a database of candidate profiles. source code, video, all sorts of stuff, tail scale VPN data. Unclear how much of this is real. They could be faking it. I don't know where the comments are, but the risk is that if there is some sort of

Starting point is 00:45:51 Equifax style payout, that could be extremely costly because if they have millions of people in their database and they've got to pay everyone 400 bucks, like Equifax did, because they have sensitive information, that could be very, very expensive. Well, we have had the Mercor folks on the show. many times and are hoping that they get through this smoothly and everyone's yeah absolutely brutal i mean it's it sucks it sucks first and foremost for all the individuals yes who's p iii is now

Starting point is 00:46:22 potentially floating out there totally uh it's probably quite bad for their customers yes paid for uh paid for the you know some amount of this data and now it's just floating out there yeah yeah and then obviously, you know, unfortunate for the company. But it's still unclear. I was looking up LAPS, which is styled as LAPSUS with a money sign, classified by Microsoft as Strawberry Tempest, and more recently identified as or a part of shiny hunters, is an international extortion-focused hacker group known for its various cybertax against companies and government agencies.

Starting point is 00:47:04 The group was active in several countries and has had it. its members arrested in Brazil and the UK in 2022. According to City of London Police, at least two of the members were teenagers. Lapsis uses a variety of attack vectors, including social engineering, MFA, fatigue, sim swapping, and targeting suppliers. Once the group has gained the credentials to a privilege employee within the target organization, the group then attempts to obtain sensitive data through a variety of means, including using remote desktop tools. Attempts at extortion follow. Initially, the messaging app telegram has, been used for communications to the public, including recruitment and posting sensitive data from

Starting point is 00:47:41 their victims. The first major cyber attack attributed to LAPSIS was against the Brazilian Health Ministries' computer systems in 2021. LAPSSS gained a variety for a series of cyber attacks against large tech companies, including Microsoft and VDIA and Samsung. Following these attacks, City of London police announced that it had made seven arrests in connection to a police investigation into Lapsis, although the group had been considered inactive by April 2022, It is believed to have reemerged in September 2022 with a series of data breaches against various large companies through a similar attack vector, including Uber and Rockstar Games. With subsequent arrests again by City of London Police and Brazilian Police, the group appears to have become inactive after September 2022, with members perhaps dispersing to other groups and a conviction of two British members. It's also interesting because they don't enforce, they don't enforce, like, brand intellectual property around hacker collective.

Starting point is 00:48:37 And so anyone can pick up the brand and use that, whether or not they're in the organization. It seems very fluid. But good luck to everyone who's working on their response and hopefully a good resolution that is resulting quickly. Let's move on to some good news. We will be having Sebastian Malibai join the show at 1230 today. But Colossus Magazine published an exclusive chapter from the book, which Tyler has there, the biography of Demis Hesabas from Google DeepMind. And he secretly built a hedge fund inside of DeepMind trying to beat Jim Simons.

Starting point is 00:49:17 Google shut it down. So there's this interesting screenshot that Colossus shared. Hasabas, for his part, assembled a secretive hedge fund operation within DeepMind. He recruited a team of 20 researchers to train high-frequency trading algorithms and explored a collaboration with the Wall Street behemoth BlackRock. It was not a project of which Google approved. But Hasabas, a five-time world games champion at the International Mind Sports Olympiad, sick, hoped he'd found another game that he could win. One day, I asked about the story of this trading project.

Starting point is 00:49:51 I was told that Hasabas wanted to beat Jim Simons, the mathematician who founded the wildly successful algorithmic hedge fund Renaissance Technologies. Rentech operated in secret, which Demis loved, my acquaintance explained to me. Did the secret deep-mind trading team make money, I wondered? No. came the answer because of Google's weariness. It was quietly disbanded. I heard about something, maybe it wasn't this deep mind team. Dave says, but did they rip Sigs? Oh yeah. Could have been the missing ingredients. Jimmy Simons. He also never wear socks and always speeds and just pays the tickets

Starting point is 00:50:24 because his, his like risk-adjusted value in terms of his opportunity cost is that he should never drive the speed limit, which is sort of a wild move. True, true wild man. I heard about the potential of Google Hedge Fund years ago. I don't know if it was related to DeepMind though, but just the amount of cash they have on the balance sheet, like they need a trading desk, basically, to move that money around. Even if they're just buying treasuries, they need a strategy, Forex, there's so many different operations.

Starting point is 00:50:53 And there was a pitch I heard about years ago that they were thinking about, like, should we be more active? We have a lot of information. We have a bunch of great engineers. We could build a hedge fund here. But they decided that it was not compatible with like the don't be, evil philosophy. It was not core to the mission and that they, you know, at some point, there is risk associated with active trading. And so you could potentially blow up. There are

Starting point is 00:51:15 certainly plenty of examples of hedge funds that had fantastic teams, but could not stick the landing and wound up, wound up zero. Sophie says Google shutting down a deep mind hedge fund quit right before they were about to get it big. It really is this meme. They probably would have printed. Although it's not like the high frequency trading firms are not using AI or not using, I mean, Jane Street invested in a custom server company or custom silicon company, something along those lines, specifically for high frequency trading. So they have a lot of, you know, AI researchers there. And you see this with a lot of the labs saying, hey, does anyone from the high frequency trading industry or quant finance want to come work over here? we can maybe start matching your salary, maybe give you a more interesting project that you can actually talk about and people will be potentially excited about. I don't know. Anyway.

Starting point is 00:52:16 Bone GPT, the rapper Eater shared. I don't want this part of my brain to grow, which is a quote from this. So in the weeks after the presentation, the two sides finally converged on a flushed out version of the Pichai plan. Sullyman would lead deep minds applied side from within Google while Hasebis would run research as an independent global interest company. For Suleiman, this was a triumph. Google had finally signed a complex term sheet granting most of what he wanted. Hasebis was equally pleased. The plan guaranteed him an astronomical $15 billion in Google funding to sustain

Starting point is 00:52:50 AGI research over the next decade, and it would put an end to the meetings on corporate structure, which he found screamingly boring. After two years of negotiations, he had hit his limits. I don't want this part of my brain to grow, he often said, when asked to get his mind around another legal document. That's hilarious. That's a great saying. I don't want this part of my brain to grow. It's so funny that, you know, you're going through two years of negotiation. They're like, okay, you're going to be, you're going to be, have so much funding to build AGI.I. 15 billion dollars. You're like, oh, so like a seed round for like a neolab? Like, great. Oh, so like one data center from a neoclacry? It's like the numbers have gotten so, so big that 15 billion does not feel like anywhere near enough at this point. Colossus hit it. Hit me, John.

Starting point is 00:53:46 Let me tell you about Railway. Railway is the all-in-one intelligent cloud provider. Use your favorite agents to deploy web apps, servers, databases, and more while Railway automatically takes care of scaling, monitoring, and security. Elon Colossus shares. Elon has spent a decade trying to control an AI lab. He tried to absorb deep mind into Tesla in 2014 and Open AI in 2018. When that failed, an intern spoke up. It did not. Interesting.

Starting point is 00:54:11 Okay, let's read through this. He also tried to control XAI to some degree. Well, doesn't he control XAI? Well, he controls it, but at what cost? I guess. All seven co-founders gone. Oh, true, true. That's what you're referring to.

Starting point is 00:54:25 Got it. Anyways, from the book, pushing back against Musk's obsession with the against Google and DeepMind, Brockman added, it doesn't matter who wins if everyone dies. Musk responded the next morning at 3.52 a.m. He confronted Brockman with a proposal that recalled Pichai's pitch. Open AI should spin into Tesla. Initially, Open AI's team could accelerate Tesla's development of autonomous vehicles.

Starting point is 00:54:47 Next, it could use the profits from self-driving cars to fund its AGI moonshot. Tesla is the only path that could even hope to hold a candle to Google. Musk declared even then the probability of being a counterweight to Google, is small, it just isn't zero. Back in 2014, Musk had Skyped Hasebis from a closet in L.A. What a funny. Proposing that Tesla or SpaceX should absorb deep mine. Almost exactly four years later, the new version of this proposal played into Altman's hands. It proved Musk's power hunger. With little difficulty, Altman now persuaded Brockman and Sutskiver to take his side. Together, the three told Musk that opening eye would not attach itself to Tesla. At an all-hands

Starting point is 00:55:27 meeting on the top floor of a converted truck factory that housed Open AI, Musk announced to the employees that he was quitting the lab, scornfully adding that... I need raptors. I need a new Ford Raptor, potentially every day. We got to put this lab above a truck factory. Inside of a. Trump factory. This is amazing. Scornfully adding that OpenA. would have to sprint faster to stay relevant. I guess they did. Hoping to lure away some researchers, he declared there was a much better chance of building AGI at a strong business like Tesla. Showing courage or perhaps just youthful innocence and intern asked Musk if speed might be reckless from a safety perspective.

Starting point is 00:56:04 Besides, it wasn't developing AI at a for-profit company like Tesla, the same as creating it at a for-profit company like Google. Isn't this going back to what you said you didn't want to do? The intern demanded, you're a jackass, Musk retorted, then he stormed out of the meeting. That intern? Tyler Cosgrove. No. That intern was Steve Jobs.

Starting point is 00:56:27 That intern was Taylor Swift. It is, it is, my interesting read on this is like, it's, it's crazy that Elon was interested in, in basically buying all of deep mind, absorbing all of deep mind, and then four years go by, and he's like, I'm, I still want a lab, I want to absorb all of Open AI. Instead of just incrementally adding to an internal lab at Tesla, just one real. researcher at a time. Like, he was able to assemble eight. They were already working on self-driving. Yeah, and he was able to assemble eight co-founders at XAI. Of course, like, they wound up leaving.

Starting point is 00:57:04 But if you just think about it as like, okay, there's going to be some churn. Maybe the churn will be higher even. But if you start the process in 2014 and you're hiring researchers continuously and using cash flow from Tesla to fund that. And then, yes, researchers might leave. But then you get new ones and you're just building that capability. It's like the Supercharger Network or Starlink, like you have to build a team and you have to continually add. But instead, Elon's been in this world where it's always like all or nothing, which is a very odd strategy to me.

Starting point is 00:57:37 Instead of just like homegrowing it. I don't know. It is just like an interesting strategy, I suppose. Let me tell you about the New York Stock Exchange. Want to change the world, raise capital at the New York Stock Exchange. And let me also tell you about Figma. agents meet the canvas your AI agents now create and modify your Figma files with design system context in beta starting to go and without further ado we have our next guest in the restream waiting room let's bring in Alex from Project 11 to the TV panel channel Alex how are you doing I'm gonna be here guys is it over or are we back what's going on how bad is it tell it to me do you have it to me straight how long do I have

Starting point is 00:58:16 Well, according to Google, you have until 2029. Okay, that's like forever. That's forever in my mind. Yeah, although maybe not forever if you think about blockchains that take a long time to change. Bitcoin's last upgrade took four years and that's a lot of 2029's listed four years away. Yeah, that seems really risky. Take us through like what actually changed because I feel like that. A little context.

Starting point is 00:58:42 We love some background on you and Project 11 and then we'll get into. to all the papers. Yeah, all good. Yeah, so me, I'm a former Army Green Beret. I got out, or I got really interested in Bitcoin working in the Middle East. Got out, went to tech. Thanks. Nice, nice sound effect.

Starting point is 00:58:58 Got out, went to Stanford, and then he got a job working in venture first, then entered the blockchain space at a company called ALEO, where I was after five years before getting really excited about solving this quantum problem that blockchain space. So that's what that led me to Founder Project 11. So in Project 11, I kind of gave it away. It's all about securing digital assets. on blockchains into the post quantum future, right? So the way I like to frame it is that what quantum computers threaten is the underlying foundation of cryptography that all blockchains are built on, right?

Starting point is 00:59:27 So it's that level that we have to fix. And then ultimately, everything on top of that, as you guys know from tech, like there's all kinds of dependencies at each layer of the stack and we have to rebuild the whole stack. And that's what Project 11 is all about. Just to put it into perspective, when did you found Projects 11? You said it was five years. You spent five years at the last company. When did you actually get started on this? October 2024, so just over, I guess, almost a year and a half ago.

Starting point is 00:59:52 And what was the general dialogue around quantum and the risk to crypto at that time? That it wasn't real. That quantum computers were always going to be 20 years away, that no one had to pay attention. There were bigger things to worry about. Honestly, I feel like that's slowly changed. And I think today's not just so there's a paper from Google. There's another paper out of Caltech, both drops. on the same day, both effectively lowered the bar massively that a quantum computer had to clear

Starting point is 01:00:21 to be considered cryptographically relevant to threaten Bitcoin. So that was the breakthrough. And I think this is a watershed moment where really at this point, when Google, the head of the Ethereum Foundation and a Stanford cryptography professor all pound the table and say, we cannot wait to migrate anymore, that people are going to start paying attention. Okay. What actually changed? Because it doesn't seem like the number of logical qubits or physical qubits, like that seems to be growing exponentially. But even when you trace out the curve, you're five, ten years away from what we thought we needed. So is this a new algorithm, a new stack of code, or is it new math? What changed that we got this 20x increase in efficiency in terms of cryptography? breaking via quantum computers?

Starting point is 01:01:13 Yeah, a couple things. So first off, these two papers are not necessarily about a quantum computer that's bigger or more capable, right? So they're about what it takes to break cryptography, right? And so what changed? So one of the things that changed was that interestingly, physicists and, you know, kind of quantum cryptographers that looked at this problem for a long time studied an algorithm called RSA.

Starting point is 01:01:34 It's not worth defining, but it's kind of an older cryptographic algorithm. But that's not what really any blockchains use. because RSA keys are very large, right? So it turns out, and this was kind of the key, one of the key upshots of the Google paper, it turns out that if you actually focus on the cryptography used by Bitcoin, Ethereum, and other networks, it's actually way easier to break

Starting point is 01:01:53 than they thought it was compared to RNSA. So that is one of the major things. The other big breakthrough, and this is from the other paper from Caltech, is that quantum computers, as you guys may or may not be aware, as your audience may not be aware, are very fragile generally.

Starting point is 01:02:08 So to be useful, they need to have what's called error correction applied. And that error correction can kind of result in a lot of overhead. You need to have tons of physical cubits to get to, you mentioned logical cubits to get one logical cubit. Well, this Caltech paper basically showed, hey, we have some new ideas to do air correction. And it turns out if we apply those,

Starting point is 01:02:28 we don't need hundreds or thousands of physical cubits. Maybe we just need a handful to make one logical cubits. So the title of their paper, actually, the headline is, you may only need 10,000 physical cubits to bring. break short to run Shores algorithm. And by the way, they demonstrated last year 6,000 humans. Okay. So we're close. Yeah. That's, you know, no one can put a timeline on it, but how fast do you think can close that gap? Yes, is the question. Okay. Uh, is it possible? Jordy was thrown out the idea of someone having a secret quantum computer going around the

Starting point is 01:03:01 blockchain, uh, siphoning Bitcoin from, you know, cold wallets that haven't moved. I'm not, wasn't implying that it exists yet, but is it, implying the incentive of if somebody were to create one of these, but, but, but yeah, the way you're reacting, I'm imagining, it's like, if, if somebody does it, it'll be Google first, which is maybe a good thing. I don't know. It's like, it's really hard to know how it's going to play out. I read a whole blog post on our, on our blog on Project 11.com, people can check out called Quantum War Games. And it was really fun because it's exactly, it's like the what-if scenarios, right? You know, because why do people want quantum computers generally? Well, they're great for science. Two, like you can imagine governments that

Starting point is 01:03:39 want to do espionage might want the ability to break cryptography too they probably don't want to reveal what they have certainly not if it's china or russia right and um you know but and private companies maybe not google maybe some of these pure play quantum companies like how are they going to make money well one way would be to recover satoshi's bitcoin as if it were buried treasure right you're like oh it's buried treasure like satoshi's not here it's mine now right so i mean that could be another scenario um so look i think that there's just a whole bunch of uncertainty about how this is going to play out about who's going to execute the attack, about how long a quantum computer will take. And again, because blockchains like Bitcoin fundamentally rely on this cryptography, like it's existential for them.

Starting point is 01:04:19 That's one of the reasons, like I founded Project 11 and we pursue this, you know, solving this problem very vigorously, is because everything's on the line here. And we have to solve it for these chains like Bitcoin have a future. Yeah. Is there generally low optimism right now that Bitcoin developers will be able to react quickly enough? What's the statement about, like, I think Churchill said about democracies or the Americans, maybe where it's like they'll do the right thing when every option is exhausted. I think this is, look, I think this is true of decentralized networks like Bitcoin.

Starting point is 01:04:53 I mean, their greatest strength is the fact that there's no single party that says how it works or how it should work, right? And this is encoded into how it was built by Satoshi as a reaction to the great financial crisis, right? So that's a great philosophical strength in the face of a. crisis like this that demands a massive technical effort to overhaul, it's a daunting challenge. Because unlike, say, Google, which Google has said they're going to upgrade all their systems by 2029. That's just, you know, someone at Google can make that decision snap, right? In Bitcoin, because it's a distributed community, everyone's kind of first has to agree there's

Starting point is 01:05:27 even a problem. Then everyone has to agree on the solution. But I think there's examples of places where blockchains, like, you know, I'll take Ethereum, have done amazing things, right? So one is they transition from an old system of consensus called proof of work to a new system called proof of state. It took four years, to be sure, but it involved thousands of people out of the world. And they did it. They did it. The blockchain's been running. Ethereum is second large blockchain by market cap.

Starting point is 01:05:49 So I don't think it's impossible, right? But I do think, especially in light of these two papers, these two breakthroughs, you just can't stop or you just can't wait anymore before starting that process. What about the rest of the digital world? because if Bitcoin is having problems, then so many other kind of core institutions and companies, organizations, I imagine, would have issues as well. Maybe because they are centralized,

Starting point is 01:06:21 there's easier to react, easier to kind of lock things down, but still need to upgrade overall encryption. Yeah, there's no doubt that other institutions need to upgrade, but in my mind there's also no doubt that, you know, blockchains and digital assets are just the most vulnerable. I mean, one, one reason is obvious. I mean, Satoshi, uh, Satoshi is Bitcoin, so the founder of Bitcoin, who we think has gone away or died or something, you know, they have a bunch of their early Bitcoin that hasn't moved. There's a bunch of lost coins. You know, all in all, you know,

Starting point is 01:06:51 it's about to maybe 15% of all of Bitcoin supply is estimated to be lost. I mean, that's hundreds of billions of dollars, uh, potentially in, right? And, you know, in market terms. So that's just a huge incentive that like, let's take, let's take the counter example of, you know, if someone wanted to hack into a bank or something. And as you pointed out, banks are centralized. They can kind of react. Also, the cryptography, the way that banks implement this cryptography is just kind of one of many layers of security, right? So it's kind of this breaks. Like theoretically, someone tried to wire all the money out of my account, my bank would call me.

Starting point is 01:07:21 Yeah, no, they literally have tape drives where, you know, they have cold storage. They print things out and they have a ledger and they can potentially roll back, which is crazy to think about. But like they could if there was like a catastrophic hack, they could be like, look, everyone's just going back to yesterday's accounts. And, you know, that's better than the chaos that we were in. That's it. And that's not true for Bitcoin. All I need is one signature and all of Satoshi's or Coinbases or Binances, Bitcoin is mine. There's no fallback.

Starting point is 01:07:50 There's no anything. And that's how it was designed. That's the point. That was the point. Permissionless finance. Yeah. That was. So that's the challenge.

Starting point is 01:07:57 So what is the state of the more fast? moving coins, faster moving chains. Are you consulting or do you think you'll plan on launching something yourself that is quantum secure, quantum proof? How do you think this plays out? Because it does feel like, you know, I'm optimistic that I'm rooting for Bitcoin. I hope the devs figure it out quickly. You know, hopefully that happens.

Starting point is 01:08:23 But it does just feel in terms of like the marketing of a new project, there is a bit of a white space. to say, we're the ones that are taking this particular feature most seriously? Yeah. Look, I mean, it's kind of hard to know how things are going to play out, but the white space that we're occupying is we want to be the bridge for digital assets to the post quantum future, right? Now, that doesn't necessarily rule out potentially having a platform to issue on top of at some point. But I think for now our priority is more or less, you know, people have already decided that things like Bitcoin and Ethereum and Solana and stable coins have value. And I think overwhelmingly they would like to keep the things that they already value and just make them secure.

Starting point is 01:09:06 So that's what we focus on. And there's no shortage of things for us to do because the protocols all have to get fixed. All the smart contracts have to get fixed. All the apps have to get fixed. And then all of the user wallets have to get fixed. And so, again, going back to the fact that this is a stack and you're breaking the bottom part of it. So, I mean, we really focus all the way across. So we've done work with Solana, the Salana Foundation.

Starting point is 01:09:25 We did the first post-quantum test net for them. We've worked with a few other protocols as well. We designed actually a new novel post-bunum algorithm designed for blockchains with the founder of Zcash. We've done that too. We collaborated with the EF. And we're getting ready to launch our own post-quantam wallet as well. Yeah. Talk about the information flow.

Starting point is 01:09:43 How much of the work that you do, the work that will be done by the Bitcoin Foundation, Ethereum Foundation, all the different developers, how much of that is open source by default or license? sensible or just can be understood by other parties and implemented very quickly? Like, how should we expect diffusion once this problem is solved to actually roll out? Will it just be like, oh, yeah, like we're just following the Salana standard. And so we're just going to mirror that over onto, you know, whatever chain we're working on. Yeah, I think there will be diffusion. I think there will be, you know, consensus, if you will, around a certain subset of post-quantum algorithms. But I don't think it's just, you know, one and done because Solana is a very

Starting point is 01:10:29 different system than Bitcoin, right? Bitcoin's digital gold. It's sort of meant to be slow. You know, and there's no apps on it. Salana's meant to be fast, right? Yep. And so the cryptography that works for Bitcoin might not be this cryptography that works for Solana. And this is actually, it was kind of the results of some of the experiments we ran with Solana. And look, this is one of the challenges, right? And this is, again, by why we keep saying this is like time to start as now, because we don't know how long it's going to take the migrate. Because, you know, these new algorithms, there's tradeoffs that come with them. And by the way, even if you choose to implement one, you need to test it and you make sure it secure,

Starting point is 01:10:59 all this stuff. So have you tried to quantify or guess, estimate what the quantum discount rate is on Bitcoin right now? Because it's an interesting thing where, like, if you own a lot of Bitcoin, there's a bunch people on the timeline today talking about this, they don't have an incentive to like really freak out and spread the narrative, but they have some incentive to say, like, hey, we need to have a conversation. We need to make progress on this.

Starting point is 01:11:22 But do you think that's factoring into price at all? Totally. I mean, the way I would put it is, I think if this risk didn't exist, Bitcoin would be priced significantly higher. So I think exactly what you said is right. You're like, oh, I'm not going to sell my Bitcoin because, you know, I mean, it's maybe not right around the corner. And I'm hoping people fix it.

Starting point is 01:11:42 But I also think there's people that would maybe enter. And they're like, you know, and Chimov has said this exact thing. He's like, hey, is this really digital gold? with this quantum threat hanging over everyone's head. So I think if that threat was removed, then you know, you remove this cloud over that ecosystem and potentially, you know, you have a lot more people coming in and therefore price would be up. Yeah. And it's easy to imagine as you approach that 2029 mark, more selling pressure, more concerns if meaningful

Starting point is 01:12:11 progress isn't made in the next two years. What countries have the most kind of advanced quantum projects outside of the U.S.? I can guess China's investing heavily here. Do they have their own retail quantum companies that are trading like crazy? What's going on over there? Yeah, first off, I think definitively the leaders, both companies and research, is American. So I think we should be proud to be an American here. But look, I think one interesting thing about the way China has chosen to attack this is they've made quantum computing a priority.

Starting point is 01:12:49 And what that means in China is, you know, it's like there used to be a lab at Tencent and at Baidu and a few other places. And at some point, a Chinese Communist Party official came in and said, guess what? You guys all work for us now. And guess what? You're all working together now. And guess what? You're not allowed to talk about it anymore. And that's the state of things.

Starting point is 01:13:06 It's kind of a, I don't want to say Manhattan project, but it's like that level of secrecy in China. and there's a legitimate question around how far back they are. So the best estimates that we have from quantum, like we have a quantum physicist who's an advisor to Project 11 that, you know, tracks generally resource estimates across the world. And their view is that China may be six to 12 months behind at most. And so this is, yeah, exactly, that's not that far. Yeah, that's really true.

Starting point is 01:13:32 You know, and so can we expect, you know, quantum computer in the hands of the Chinese Communist Party that maybe is more willing to crush dissent in places like Hong Kong to carry. much about the philosophical principles of Bitcoin and decentralization if it serves their purposes to do otherwise. I don't think we can. And so I think, again, back to the fundamental problem uncertainty, right? And it's better to be safe than sorry. So we need to basically prepare today to prevent the crisis tomorrow to keep the trust in these systems. Well, thank you for everything

Starting point is 01:13:59 that you're doing. Thank you for your service, both here and before. Project 11.com is the website, correct? Yeah. Yeah, you got it. All spelled out. Yep. Fantastic. Thank you so much for taking the time to come chat with us. We'll talk to you soon. Appreciate you in the breakdown. Have a good one. Great to be here, guys. Thanks. Cheers. Goodbye. Let me tell you about Vanta. Automate compliance and security. Vanta is the leading AI trust management platform. And without further ado, we have Kacer Eunice in the Restream waiting room from Applied Intuition. He's the founder and CEO of the company. And we'll bring him in In just a second.

Starting point is 01:14:39 We need a little bit of time. A little bit ahead of schedule. A little bit ahead of schedule. We need a little bit of time. And it's hard because there's not all that much short-term news. There is one news item that we can go through quickly. All birds just sold for $39 million. The company was once worth over $4 billion with D to C darling.

Starting point is 01:14:59 Followed this company closely because I was building a D to C company at the same time. I was like, wow, they are really getting big. but it seemed like it did not particularly scale. It was more of a niche product potentially. And of course, you know, margins and cost of sales creep in. And then everything collapses to private equity multiples. Did you ever wear a pair of allbirds? Were they ever ever pull you away from Botega, get you in some allbirds?

Starting point is 01:15:27 You know, it's Australian wool. You know, it's kind of like Italian leather, Australian wool. Yeah. There's something like that. never, I never, I never, never throw a pair of birds. Not even if you're visiting San Francisco. It's a great, it's a great sign of respect. Did you ever, did you ever have a pair? I had probably did. I think I had one pair at some point. Um, they were okay. They didn't, I don't know. They, they, they, they sort of like look okay and or comfortable on day one, but then they

Starting point is 01:15:54 sort of deteriorate a little quickly. Look, this would be probably two to three trillion dollar company. Mm-hmm. If the shoes had aura. Yeah. But they, they, they, they, they had, They should have released a line. They actually had, it seems like they potentially had negative ora. Yeah. And they got, I mean, the stock suffered. They had to pay the aura tax. The aura discount.

Starting point is 01:16:16 Massive aura loss. Yeah. I mean, still a very interesting launch, very interesting go-to-market, telling the story of where the materials are from. That was certainly a playbook that was adopted by a lot of companies. Showing, putting the supply chain onto display, basically. It was the right, very fit at the time. People are not into it.

Starting point is 01:16:37 The chat is not happy about... Let's ask our dear friend. Kayser, Eunice, from Applied Intuition, because he's here. He's in the TBPN Ultradem now. Cacer, how you doing? I'm doing great. How about you guys? We're doing great.

Starting point is 01:16:52 We have to ask, do you own a pair of allbirds? What's your preferred shoe when you're walking around a factory like that? I don't own any allbirds when you're in a factory. you're going to have to wear. Yeah, exactly. There's no allbirds. Maybe they should. Maybe that's the comeback story for them.

Starting point is 01:17:12 So they just, they were worth $4 billion. Now they're worth $40. Maybe the steel toe allbirds are what gets it done. A steel toe all bird would look fantastic. We seem to be having a video delay. I think the team will work it up, but we can hear you.

Starting point is 01:17:24 Can you hear us? Okay, great. Yeah, I can hear you. I can see you okay. Okay, fantastic. Exactly what's going on. Well, great to have you back on the show. I'd love for you to just reset with us

Starting point is 01:17:34 for the shape of the business, where the company is today, how big are you? Give us the broad strokes, and then we'll go into the partnership today. Yeah, thank you. Thanks again for having me. The company applied in tuition, we're a $15 billion company still doing

Starting point is 01:17:50 what we were doing before, which is taking intelligence and putting into physical machines. Today we have our first ever physical AI day where we're bringing lots of investors together, bringing industry analysts, You know, bringing everybody who's kind of relevant in the field to talk about all the things that are happening in physical AI. We're pretty strong believers that the future, you know, the next kind of big thing is AI going out of screens and going into the real world.

Starting point is 01:18:18 Yeah, I couldn't agree more. Talk about the most recent partnership, LG. Yeah, LG Intertech. We just announced this a couple of days ago. I don't know how many of your viewers know, but LG provides... I'm putting AI in TVs. That's what you're doing. The AI is going in the TV, and I'm going to be able to ask questions.

Starting point is 01:18:39 The smartest, the biggest. No, that is not what we're doing. Much more serious. I mean, what's happening in the self-driving space is there is, now the models are basically working and they're figuring out. So really, there's an aggressive downward pricing pressure of how to make self-driving cheaper. The research kind of question is done, and now it's just an engineering question. And that's just another way is saying it's a cost question.

Starting point is 01:19:04 So companies like LG who are doing, you know, sensors at really, really large scales and really, really cheaply, you know, they're entering the space as well. We're working together with them on self-driving. Yeah. So, yeah, take me through. When people think self-driving, they always think Waymo, Tesla. But the market map of like products that need autonomy and that would be defined as vehicles. Give me some examples. I mean, you're standing in front of something.

Starting point is 01:19:35 I know that it's very broad. What's in this partnership and then what else are you focused on? What's adjacent and what's, you know, on the roadmap? Yeah. So I think what's different about us versus, let's say, vertical players like a Waymo or a Tesla is we provide this, you know, AI across all types of machines. So you see ag machines behind me. if you were, you guys were here for physical AI day, we do, we take the same models and we put them in defense.

Starting point is 01:20:04 We put them in commercial trucks. We're running driverless trucks in Japan right now that are going into commercial operations in the next quarter. We are running in mines. So both all the way from, you know, Arizona to Australia. So our hypothesis basically is these, these technologies, what is self-driving or the underlying operating system, they're so expensive and they're so complex to build.

Starting point is 01:20:29 Yeah. and maintain, the only way that you really make this a viable business is that you actually spread this across lots of manufacturers and lots of industries and lots of use cases. I mean, our kind of crazy claim to fame is, you know, our company is almost 10 years old, and we've preserved basically all the capital we've ever raised. It's amazing. Which is kind of, you know, it almost sounds like BS, right? Yeah, it's crazy. The whole mantra is, you know, raise a lot of capital. And we're a real AI company. We have real AI bills. And we've figured, a commercial model, which is a lot of the scale. We have over a thousand engineers, and so we're

Starting point is 01:21:04 one of the, if not the biggest physical AI companies on the planet. That's obviously also commercially viable. But it all goes back to that simple thing, is like, you want to distribute all this cost across lots and lots of companies, lots of verticals. What about shared learnings? Is a team that's working on mining? Are they able to find a breakthrough or discover something you can apply to trucking in Japan? Like, is there a lot of... Absolutely. That is the heart of the company. And so there's all, what you described as like shared learning kind of broadly, but there's also technical advantage. What we've seen is taking data, which is just obviously also not obvious, but taking really, really diverse data from a mine actually makes our self-driving car system better. And taking data that we have from our software in car in Germany, you know, makes our defense work better. And so it really is, it really is a poor to, you know, Yeah, I've heard so many stories about that where, like, there will be, like, exactly one instance of a chicken being chased by a woman on a tricycle in the training set.

Starting point is 01:22:12 And so it's very hard for the machine learning system to actually understand that if you see that exact scenario, you got to slow down, but that's the nature of big data and machine learning and these scaled systems. And it's not, it sounds crazy, but it's not that crazy to imagine some weird scenario that you in a mine actually teaching you something that you could use just on a normal street. Yeah, maybe getting a level lower just so, because me being an engineer always bothers me to talk in peer generality, you tend to mix them, miss things. Just getting to a level lower. What you're really talking about is anomaly detection. And it's not necessarily like, you know,

Starting point is 01:22:48 you need to see the chicken running across the road in Thailand and that's going to make the mind and my better. But what's really happening is models are getting a better understanding of the physical world around them. And the kind of, for, parameters around them, if you look at, you know, kind of the last kind of generation, I'm crazy to say last generation, but really large language models, large language models really improve with diversity of data. That is really like, you know, kind of a big breakthrough. And of course, scaling laws. All of that stuff is being brought in to the physical world. Yeah. And we're powering that. Yeah, I mean, truly no one would have predicted, or, I mean, of course, some people

Starting point is 01:23:23 did predict, but I would have never predicted that, like, including poetry, would help a model get to, like, solving math. Like, I would just see those as different things. I'd say, put the poetry team over there, put the math team over there, but actually bringing all these things together worked really well. Play out the counterfactual for me. You haven't, you haven't been a high burn company. You haven't been super capital intensive. If you'd done vertical integration and built the tractor behind you, that would have been extremely capital intensive, correct? Is that like impossible? It's, well, nothing is impossible. But I, you know, my, my undergrad, was at this obscure school called the General Motors Institute.

Starting point is 01:24:02 And as the name implies, it's really about automotive. It's like the West Point for automotive. And when you spend a lot of years in factories, as I have, there are some deep lessons that get imparted into you. And one of those lessons is, holy crap, these factories are extremely cost-intent, the capital-intent, and they're extremely complex. And the strengths of Silicon Valley are actually don't fly,

Starting point is 01:24:28 with the strengths of building a large factory. Now, in terms of the core question, we had Mark and Driesen here today, and we, you know, we talked about this. Mark was one of our first investors and has kind of been, been along with us with the entire ride, I mean, all the way to the presentation today. And we asked him this question about vertical, horizontal, what do you see happening in AI? What do you see happening, specifically physical AI? And the punchline is, you know, we, all of our values that applied intuition can be reduced down to two words, radical pragmatism. And if there are verticals that we think that we should be a bit more vertical in, we'll do that. And I think it's it's kind of a false tradeoff to say what we do in, you know, trucking is what we're going to do

Starting point is 01:25:08 in construction, what we do in agriculture is what we're going to do in mining. What we're really trying to do is bring intelligence out into the real world. And each of these verticals are facing really, really different problems. You take, you know, with a tractor behind me, the average American farmer is 58 years old. There's nobody coming to replace that person. And So what is going to happen? Because, you know, if you take that person, their kids have left, and they're often not coming and taking over the farm, like maybe in previous generations. So that farmer needs, you know, we don't need to teach them how to use Claude Code.

Starting point is 01:25:41 That's not what's going to change the farmer's trajectory. What's going to change the farmer's trajectory is the machines are intelligent and they're working harder and smarter on their behalf. And so he can run an entire farm with a, you know, with a swarm of machines. And that's not, you know, that's not too far into sci-fi. One of the key components here that we're doing, and we believe, is you need to abstract that hardware and software way. We as technologists, you look at like your laptop and your phone and you kind of take for granted the miracle that exists. Android runs on thousands of hardware devices flawlessly.

Starting point is 01:26:15 So that's also something that apply. It does it. We're just abstracting the hardware and software. Once you do that, you can make every machine, you know, intelligent. Have you tried to estimate the economic? impact, assuming you guys, you know, stay at the, you know, at the current kind of improvement rate or accelerate as the technology kind of starts to diffuse in some of these industries like trucking and mining and agriculture. Like what are the downstream impacts? I mean, there's such a

Starting point is 01:26:43 debate right now around what impact will AI have on the economy? So much the economy is like moving physical things around, producing things, shipping them. Let's separate. Exactly. Let's separate Because economy is such a generalization. So when you're talking about code complete and white collar work is very different than trucking where there is a huge labor shortage, it's very different than in mining where people don't want to go live in kind of remote areas doing 12-hour shifts. I mean, literally labor shortages are preventing construction companies

Starting point is 01:27:18 from collecting billions and billions in revenue. So these are industries where AI can't get there fast enough. It's a very different calculation. than a kind of, you know, I think what the normal narrative is. And then we're super obviously excited about that. Let's take defense as a particular example. It's a very salient example. We don't need more warfighters in harm's way.

Starting point is 01:27:39 We need less war fighters in harm's way. And no warfighter wants to go out into that ecosystem where autonomy is really becoming the dominant thing. And so I think the way to think about this impact in the physical world is it's a lot less resistance. There's a lot more pull. Now, the first question you asked is the size of impact, I don't want to, you know, sound like I'm pitching my own book here with, you know. I'm asking you. I'm asking you. I want the biggest number. I want the biggest number.

Starting point is 01:28:07 The numbers are absurd and ridiculous. But I can tell you this much. If you think about, you know, the way I think about, you know, I used to be a Y Combinator before I was the CEO and, you know, ran the firm and funded lots of interesting companies. And one of the analogies I used to help founders understand market potential. market sizes. I grew up in Detroit. You're sitting in the Detroit metro airport and you're sitting in a gate. You look around. How many of those people are like really deeply using Claudeco? I mean, frankly speaking, not many. Now, a lot will probably be using something like ChatGPT, some variant of that, maybe Gemini. But how many of those people drive? How many of those people work at construction sites? How many of those people ride in buses? How many of those people serve in our armed forces? The point is a much, much, much,

Starting point is 01:28:54 larger group. And I feel a little, again, the engineer in me feels a little awkward saying these kind of pitching these things, but I think the market for physical AI is way, way bigger, purely because the surface area is much bigger. And it's compounded by the way that, the way technology diffuses with phones and laptops creates this like rabid, you know, competition that you see in, you know, that you're seeing in all these kind of subspaces, right? In physical AI, you've got to kind of know what's going on in the car business. And I'm not saying, I'm not gatekeeping and saying, yeah, you've got to go to the General Motors Institute to build technology for the car business. But you bet your bottom dollar, it helps.

Starting point is 01:29:36 And we're doing that across a bunch of industry. I think it's, you know, I'm as confident about the companies ever before. You know, the question, we always get asked this question. Why the hell did you raise all this money, you know, almost a billion dollars? He's going to keep plowing away in the bank account. We're doing over a simple of a simple reason. Because if we need to, we can invest very aggressively to take opportunities that we think we can accelerate, you know, beyond just traditional organic growth. And so far, that's worked.

Starting point is 01:30:00 It's not to, you know, promise the future that we won't. But those are kind of debates we have every single day. Yeah, that makes sense. Well, thank you so much. I just want to say I can see the path to $100 and then a trillion dollars in run rate. I agree. Well, I mean, Waymo, you know, a company that, we love them. They're a local, you know, we're also in.

Starting point is 01:30:21 Mountain View now Sunnyvale. That company, you know, is a great company, but is burning a lot of capital and is smaller revenue base than us and just raised at $126 billion. Oh, okay. I mean, I love those guys. I mean, we have so many friends there. I'm not, I'm not trying to talk poorly about this. No, we love Waymo, too. It's very impressive what they're doing. You know, 15 that we're at and 120,000. I think I think you got room to run. Massive, massive. Yeah, Tell Mark, tell Mark, you're ready. You're ready for the thing on. Believe, believe me, everybody wants to show, you know, it's a word.

Starting point is 01:30:58 I feel like it's faux-gawa where they want to keep putting money, you know, money into the company. We don't need any money. That is the best analogy for Avenger Capitalists. Yeah, yeah. They are the farmer stuffing the goose. We have our own, we have our own farm, you know, and we're making our own money, so that that's really great. And frankly speaking, I mean, like I said, Waymo is great, but it's just robo taxis. Yeah, yeah. And that's a small, it's so much broader.

Starting point is 01:31:24 Go, go to, go to Warren, Michigan. Yeah. And you just go to the party shop in the corner and say, hey, are you excited about Waymo? I don't think, you know, it's not hit the masses yet, which just shows obviously Waymo's growth potential, but also shows, I think, how big physical AI is going to be. Yeah. Well, thank you so much for taking the time to come chat with us. Thanks for having me again.

Starting point is 01:31:44 Yeah, fantastic. And we'll talk to you soon. Thanks. Goodbye. See you. Let me tell you all about public.com investing for those that take it seriously. We've got stocks, options, bonds, crypto, treasuries, and more with great customer service. And we're talking to them later today. But first, we have Sebastian Malibai. He is the author of The Infinity Machine. Sebastian, how are you doing? I'm doing great. Thank you. Thank you so much for time. So great to have you. This has been, you've been on John's dream guest list for a long time. We met maybe four years ago at a talk you gave around the power law.

Starting point is 01:32:19 And it was very fascinating. I love that book. This book goes in a different direction. And after that conversation, I asked you, probably the worst question you could ask to an author, I asked you, what's your next book going to be about? Because you had selected venture capital. Venture Capital had done very well. And I presume that whatever you would pick would be a great investment category because You seem to be a good picker.

Starting point is 01:32:46 You told me that you were thinking about biotechnology, biotech investing. You went a different direction with AI. Is there anything I should read into that? Well, I always kick the tires on a few ideas before I settle on one. And I think it took me from the parallel coming out in February of 2022 to somewhere around the summer, maybe August, when I really settled on AI. And then it took me another, I don't know, three months to get the courage up to go and pitch Demis Asabis on the idea of giving me a ton of access so I could write this book. And then I got lucky because I pitched him.

Starting point is 01:33:25 And one week later, guess what, chaty PT came out? So what I thought was maybe a fringe subject went mainstream, super fast. Super fast. What was the response with the team? What was the process? Obviously, he's extremely busy. He also sleeps at very random times. get into that, but what was your actual interaction? How much time did you spend? What was the

Starting point is 01:33:48 research process like? So once he agreed to be in, he was really in. It took about six meetings, two with him, four with his team, to get them to agree. And, you know, my pitch was, hey, if you say in every speech you give that artificial intelligence is the greatest invention in history, that means you're way too important not to have a book about you and it's going to happen so you better get used to it and also if you're going to upend our lives

Starting point is 01:34:18 change the way we think about ourselves as humans because it's a rival form of machine intelligence you better explain your motives to people otherwise they're not going to accept it so that was the pitch he agreed and then once he agreed we would meet like for two hours at a time we would go to a pub

Starting point is 01:34:37 near his home in North London And there was a kind of secret staircase at the back, go upstairs, kind of dusty little room with nobody else there. And we would sit there for two hours, usually. And he would just riff, you know, talk about philosophy, movies, computer science, neuroscience. I mean, he's such a range of a person, by far the most fascinating person I've ever written about. Wow. That's high praise. How do you think about balancing the...

Starting point is 01:35:09 the biographical timeline, the history, the financial impacts, which you've covered in the past. When I think about the stories that you've told in the power law about venture capitalists, there's a little bit of their philosophy, but it's a lot of how the deals came together, fly on the wall. I love that type of storytelling, but this goes a little bit of a different direction. So how did you think about balancing all the different perspectives that you could bring to his story. Yeah, I mean, I always want to do the personality, the figure, but then the landscape behind as well.

Starting point is 01:35:47 So it's always a mixture of, you know, you need a character who drives the story, but the story's boring if it doesn't mean anything. So you have to link it to larger stuff that's going on in capitalism and how society's going to change and all that. And, I mean, in this case, because Demis is who he is, and he would just riff in these extraordinary paragraphs of like storytelling and theoretical stuff

Starting point is 01:36:13 and you know it's just so fascinating that I did give him the microphone more than I have in any other book I mean I basically quote him at some length you know and it's broken up with me asking him questions and so I'm kind of the reader's lens through which

Starting point is 01:36:29 to see Dem is talking and I'd never used the first person really before in my other books but in this case those 30 plus hours I had talking in a pub with this extraordinary man, that was the gold dust I had. So to really make the most of it, I did have these passages of us talking together, which kind of interspers the more analytical or narrative bit to the book. How, after the transformer model dropped, what was Elias Gav's reaction and why did open AI get ahead?

Starting point is 01:37:03 You know, I cover all that stuff as well. but I do have these passages where you see events through Demis's eyes because I think it's worth doing because he's so unusual. What was your understanding of AI or view on AI in 2022 before you meet Demis for the first time? Are you aware of the doom arguments? Were you a believer in the technology? Did you think it was 20 years away, 100 years away, two years away? Where were you before this book? Because I feel like it probably changed you. Yeah.

Starting point is 01:37:41 You know, I had met Demis before at tech conferences because of the power law and writing about venture capital. I would go to tech conferences in Europe and he would sometimes be there. And I actually cheekily, you know, raised the issue of hedge funds and especially, you know, the one Renaissance technology is the main CEO, Peter Brown. had done a PhD with Jeff Hinton about AI back in the day. And of course, I knew that Dennis would know that. And so I said, you know these guys who used deep learning and applied it to markets?

Starting point is 01:38:17 And that got his attention. So I talked to him a bit. So I knew that he was amazing. I knew that the technology was ripe in the sense that he'd produced this string of breakthroughs, you know, AlphaGo, defeating the human Go champion, then Alpha Zero, which was even stronger. And there was Alpha Fold, which won him the Nobel Prize for predicting all the shapes of protein in nature. So there was a series of good models.

Starting point is 01:38:42 And what they all had in common was they dealt with insane amounts of data, crazy combinatorial spaces. Like in Go, there's 361 first moves you can make. Okay, that's way more than chess. And so unscrambling Go and the strategies in Go was much harder than chess. And I knew that these breakthroughs were not just cool in themselves, but they represented the coming of a time when machines could make sense of an almost infinite amount of data and extract meaning. And hence the term the infinity machine, the title of the book,

Starting point is 01:39:19 and hence my enthusiasm for writing about it. And I knew it was breaking out. I knew Demis was amazing. What I didn't know is it was going to break out literally the week after I met him and pitched him on the idea. What has surprised you about how the industry overall has evolved since you started meeting with Demis? Because in some ways, I have to imagine you kind of maybe it hasn't been that surprising at all, even though a lot of the growth is impressive.

Starting point is 01:39:48 But do you feel like you had a view into the future from those first conversations in the pub? Yeah. I mean, I think, you know, I was lucky that the meetings were bookended by going to see Demas sort of maybe the third meeting or something chat he beat up by this point had gone viral and him saying to me okay this is war

Starting point is 01:40:09 you know you could see his competitive side come out right this is war these guys he said have parked the tanks in my front yard you know I'm fighting back so you could see that and then after that comes the merger between Google Brain and Mountain View

Starting point is 01:40:25 and the deep mind team in London so the two kind of halves of Google's AI talent base are united. And then I think you get what, you know, a business school professor is in the future going to write about is kind of like a textbook case in how you make a merger successful. Because everyone knows the mergers are hard.

Starting point is 01:40:48 And when you do it with eight time zones between the two teams, one in London, one in California, and you're doing in the middle of this knock-down, drag-out, capitalist fight over building LLMs, most people said this is going to fail and I would come to Silicon Valley while I was doing the book

Starting point is 01:41:05 checking with my friends at different venture capital shops and they'd always say game over open A is one and the surprise is that within two and a half years Demisarvis' Google Deep Mine model

Starting point is 01:41:18 Gemini was doing better on the rankings than the open AI model so that was an incredibly fast to come back Yeah How do you think about the importance of being like a business person or a deal guy in AI. It feels like Demis has this

Starting point is 01:41:38 quote. He doesn't want to grow that part of his brain, referring to some legal negotiations that took a number of years. Solomon. Oh, oh, is that Musafah? That was, that was, that was Demis saying. I don't want part of this my brain to grow. And so, and so, take away these legal briefs. I completely get that. And it seems incredible for him to stay in the research mode, build the research organization, and yet because of scaling laws, we're in this weird regime, in this paradigm where sometimes doing a deal to marshal an extra 10 billion of compute actually does unlock a new capability and is almost in the research track. And I'm wondering how you perceive the relative importance or Demis's perception of the relative importance of these sort of like business dealings that might be more critical path to

Starting point is 01:42:33 AGI than the Demis of 2021 might think. Yeah, I would say that the single most important business relationship in the world today is between Sundar P. Chai, you know, CEO of Google, and Demisis who's running the AI brain trust. Because, you know, Sundar has Demis' back. He deals with providing the resources, you know, supporting the notion that you're going to spend all these tens and maybe hundreds of billions on compute. You know, that's Sundar's, that's what he delivers. And he gives Demis the oxygen to then just go do the science.

Starting point is 01:43:14 And sure, he has to build products. But I think, you know, he said to me several times, Demis, we've got to a point where building a product like Gemini is, in fact, advancing. the progress towards AGI. There's no tension between the two. If you had stopped your AGI research 10 years ago and taken a sidetrack to build some widget, yeah, that would have been a waste of time.

Starting point is 01:43:38 But now that it's so mature and you're actually, to build the next LLM, you've got to kind of figure out, you know, a reasoning model, then it's going to be a genetic and then you're going to be scaling it even more and all this stuff that we've seen. This is genuine scientific progress as well as product advance.

Starting point is 01:43:57 Yeah. Do the products also help sort of shift the culture in Google? I'm interested in understanding this concept of like AGI pilling, becoming a believer in the Demis worldview of the impact of AGI, what artificial intelligence will do.

Starting point is 01:44:17 That mindset has to diffuse through Google. The chat GPT viral moment clearly had an impact. I'm sure agentic coding has had, that has had a similar impact, but what has Demis' role been in being the culture carrier of that belief in AI progress internally? Well, I think he's used all his sort of visionary communication skills to unite the Mountain View team and the London team.

Starting point is 01:44:47 And I think the one sort of organizational contribution he's made, which is super powerful, is that from a long time ago, Deep Mind had always two different cultures going on at once. There was a kind of blue sky research for scientists. You get a lot of freedom. You could publish papers and all that.

Starting point is 01:45:05 You know, go find what you want to find. And then there were moments when Demis decided that if you pushed really hard on a particular product or a particular project, you could get a breakthrough achievement that would really shock the way. world. And so he did this repeatedly with AlphaGo and AlphaFold. And this was sort of like his judgment, scientific taste being applied to knowing when, you know, the moment was ripe to really go for it.

Starting point is 01:45:35 And once he decided that, there was, you know, the blue sky research kind of bottoms up stuff, you know, that went out the window and it became a top-down strike team, they called it. And in a strike team, there was a lot of top-down direction and kind of everybody had to work on the same code base. you couldn't just go off and code your own experiment on the side. You had to be contributing to the main one. And that drives towards, you know, a team is driving in a united way towards an outcome. And I don't think Google Brain had that.

Starting point is 01:46:06 Google Brain had, you know, much more of the bottom-up stuff. And there was no strike team component. And so Demis brought this strike team idea, and it came from video game design. You know, earlier in his life, he'd been a builder of video games. and he, in fact, started a company doing that. And so this was like how you ship product.

Starting point is 01:46:28 And that's been a key insight for Gemini. Yeah. Google and Gemini have every advantage just due to the massive cash flows that they have from their other businesses. How do you think that has impacted the culture of deep minds given that they have something very real to lose, right? It's not just about the, you know, maybe Demis's personal desire

Starting point is 01:46:51 to be at the forefront of this research. But if you're not successful, then you lose one of the greatest business, you have the potential to lose or have your kind of core business threatened. Yeah, Google search in such a big way. Yeah. And I think Google search stands for a more general point that Google's whole reputation stands on providing reliable information. And so the penalty for screwing up is very high. You've got this very valuable company, you don't want to support its reputation. And so I think they were more worried about, you know, releasing a chatbot fast. And so they had prototypes of a chatbot in the fall of 2022.

Starting point is 01:47:35 And they didn't want to release. And then Open AI went ahead and did it. And so that kind of forced their hand. But their first instinct was, this is going to hallucinate. This is going to do bad stuff. We can't afford that hit to our reputation. and, you know, Demis was quite honest with me in saying, well, you know, the surprise was actually the public's quite happy to play with the tool that hallucinates.

Starting point is 01:47:58 You know, they still went viral, you know, so we should be less inhibited. But that was an example of how being at Google could be a kind of inhibition in moving ahead. How does Demis, he's always told a very optimistic story about AI. I love him as a science communicator, as a, is a, is a, as an optimist, how is he interfaced with the effective altruist community, more of the AI Doom crowd? Does he, because he doesn't talk about it that often, but does he think about it often? He does think about it. In fact, you know, he met his co-founder Shane Legg at an AI safety lecture, right? They bonded in a safety lecture. And so right from the beginning,

Starting point is 01:48:43 safety has been a big part of the agenda. And when Demis sold his company to Google in early 2014. Part of the deal was you're not going to use this technology for weapons ever, and you're going to have a special independent oversight kind of committee, you know, which will decide on AGI deployment, because we don't want that to be just up to the corporate board of Google. Now, you know, he's slipped on some of these things, particularly the military staff. But he has been thinking about safety, and, you know, the question is, what has he got to show for it?

Starting point is 01:49:18 It's all very well to think about something, but what can you deliver? And I think, you know, this is why towards the end of my book, he's talking to me quite honestly about how it's a sort of paradoxical moment. He's doing great as an AI inventor. He's doing terribly badly as a sort of AI steward, as making it safe. It's just, it turns out that there's a race dynamic. The race dynamic includes China. How do you control this technology when everybody is racing to generate?

Starting point is 01:49:48 out the door. Yeah, it was interesting. Last week, we were talking about how Bernie Sanders has come out with a push to pause data center development. And he quotes Demis and some other lab leads talking about how they would agree to a pause if other countries were kind of in agreement on it. And Bernie obviously left out the fact that I don't think any lab lead could see China pausing on development.

Starting point is 01:50:16 How is your person? definition of AGI evolved over the last few years because everyone has their own definition. Half the people that come on the show says it was six weeks ago. Exactly. And then yet we're still in so many of these kind of more high-level conversations lab leads, talk about race, you know, where AGI is six months away, you know. You're completely right. Everybody has their own definition.

Starting point is 01:50:43 And so my solution is not to have that discussion. I mean, who cares? what, you know, this, like you could say right now, it's, Gemini is artificial, it's general, it's intelligent, game over. But, you know, just a definition thing. I think the other one, which is sort of usually fruitless is, is AI conscious? Could it become conscious? What is consciousness? Nobody has a good idea. So that's just a sidestep those things. I heard one good idea, which was something around training a model specifically that would hold back all data and all training data related to consciousness

Starting point is 01:51:16 and the idea of consciousness, and so it cannot just pull from the archive and reference or simulate consciousness, and if it develops consciousness from that and can talk cogently about consciousness without having any training data ever seen the idea of consciousness, then maybe that's conscious.

Starting point is 01:51:35 I don't know. It was just an interesting thought experiment. I don't know that anyone's actually run the test, and I don't know that I would even accept it if they did, but it is something to think. Did you feel an acceleration in your personal writing process due to AI? I felt an acceleration in my learning process, which is sort of what I do before I go interview people.

Starting point is 01:51:56 Because all of the computer science papers are basically on archive, and recently there's been less publication, but it's certainly up to about 2022, you could go see a scientist either at Deep Mind or one of the rival labs and just have a conversation with the model about, okay, these person has done four papers, what was the connecting thread, why is this person different to the one I interviewed last week? That was a super efficient way of getting up to speed, and I didn't worry that it might be wrong because I was going to speak to the human and cross-check it. But that was helpful.

Starting point is 01:52:30 Do you think Demis's having a home base in the UK is, in what ways do you think it would have helped or hurt the company so far? like has it been beneficial from the talent war standpoint? I'm sure, I'm sure some of the other lab leads have taken a trip out to the UK. Mark Zuckerberg's hosting nightly dinners for AI leads at his house, which is just a couple blocks from all the other labs. Can't do that if you're in, if the researchers are in the UK. Right, yeah.

Starting point is 01:53:04 I mean, there is movement across the Atlantic, but I think the deal is if you're in London, is a little harder to recruit people but once you've got them, they're probably stickier than they would be if you're in Mountain View or somewhere. I think Demis has stayed in London

Starting point is 01:53:19 because actually he is weirdly patriotic. He comes from this mixed up sort of a Greek heritage father, a Singaporean Chinese mother. In a way, that makes him a typical Londoner because London is really a melting pot. But he stays there because he feels he wants,

Starting point is 01:53:38 he believes, and sort of British social democratic values. It made me ironic to an American audience, but, you know, actually he thinks it's more egalitarian in Britain than it is in the US. You know, the US, if you go to the Deep Mind Office in London, you know, you go past

Starting point is 01:53:53 the sort of public spaces, like this kind of fountain with toddlers playing in it, and there's a kind of free movies in the summer by the canal, and then you get to this green space where the kids from the local housing project are playing soccer, and then you get to the Deep Mine Office,

Starting point is 01:54:08 and it's hard to imagine you'd find that on the way to the Apple headquarters or something it's just a different vibe. Could you ever see Demas as CEO of Google or what do you have to do too much paperwork? You know, this gets to the heart

Starting point is 01:54:26 of the dichotomy about Demis. It's so difficult because he's so many different things at once. I mean, you know, he is this Nobel Prize winning scientist who would love to just do pure research and he often would sort of fantasize to me about, hey, I want to retire to the Princeton Advanced Institute of Advanced Studies

Starting point is 01:54:43 and do what Einstein and Oppenheimer did before me and go there. And I think he really means it when he says that. At the same time, he also wants to be in command of an AI lab and he likes the capitalist competition. So if he had the opportunity to be chief executive of the whole of Google, I suspect he's too competitive to say no but who knows

Starting point is 01:55:12 I mean there is that science side so it's genuinely unpredictable he probably doesn't know himself were you left personally optimistic after this process about just our AI future broadly net positive impact from AI I mean clearly there's a lot of upside

Starting point is 01:55:29 especially in medicine and pharmaceutical discovery I think you have to be honest and say there's also downside, significant downside. And as I continue to do the research for this project, you know, I became more worried about the downside because, you know, people like Jeffrey Hinton, I went up and spent two hours in his kitchen in Toronto and sat there debating, not necessarily whether machines would be more intelligent humans, obviously that they will be. But whether they, whether machines have a motivation to harm humans. And he's

Starting point is 01:56:03 very persuasive in arguing that they will. I mean, my point was, look, humans evolved over centuries to survive, to pass on their DNA, we're hardwired to survive. That's why we fight each other. Machines aren't like that. So why would they attack us? Why are you so worried, Jeff? And Jeff is like, well, you know, imagine you've got this super powerful AI and it's going to be attacked by the enemy AI and you have to defend it. So you tell the AI, if you see a cyber attack coming, you've got to fight back, you've got to defend yourself, and now all of a sudden you've given your AI a survival instinct. And so don't tell me that evolution has to happen as it happened to humans. The evolution can happen in a machine way, but these systems are

Starting point is 01:56:47 going to want to survive, and they're going to be more intelligent than us. So we're in trouble. And I think you can't dismiss that. So I'm kind of both worried and excited at the same time. And I think that's how humans generally respond to all technology. And if we didn't take that trade and move forward with both the excitement and the scariness of technology, if we didn't take that, we'd be still living in caves. So in some sense, the story of Demis is like, you know, the story of all of us, but magnified 10x. There's a documentary that was just released or might be releasing right now that features an interview with Demis, the AI doc. and it spends more time talking to all the different lab leads and voices in the industry, more focused on the doom question.

Starting point is 01:57:36 Can we be apocalyptic? Should we be optimistic? But what I found most interesting was that the creator of the documentary summed up his full takeaway and said that AI is a Ponzi scheme. And I'm wondering if you got any vibes that everything will collapse, that this is just not financially viable. No, my view is that there's no AI bubble, but there's only just an open AI bubble.

Starting point is 01:58:05 In the sense that the technology clearly is getting better and better pretty fast, right? You know, we had the first chat bot in 2022, and it hallucinated, then they killed the hallucination, then they had longer context windows, then they had multimodal systems that could handle all video and pictures, and then they went to...

Starting point is 01:58:25 reasoning models and now we're getting agentic models and now next there's going to be, you know, world models that will be built into these things. This is a lot of progress in just three and hour of years. So I think it's accelerating in progress and therefore it's not a bubble. But what is true is that it's super expensive to develop. And if you're not attached to a really deep pocket like, you know, Demis is attached to Sundar, you're in trouble. Because I don't think Open AI can raise enough money to bridge from today when they have a very popular chatbot, but almost none of those customers pay for it, to some future where the product is stickier somehow, and they can charge money. And so I think Open AI has been running two simultaneous experiments. One is with a new frontier technology.

Starting point is 01:59:17 And the second is, how deep are global capital markets? and they already raised 41 billion last year which was a record for any private fundraising bigger than any IPO by the way as well and so

Starting point is 01:59:32 kudos to Sam Altman for raising that much money but can you pull that trick like on a bigger scale every year until 2030 when they hope to break even no and that's why they're cutting

Starting point is 01:59:45 products like SORO except for right now because they just raised the 120 But if you look at the 100, it's kind of smoke and mirrors. A lot of that is contingent on you get this money if you go public. You get this money in the future. You get this money in kind in terms of, you know, compute or something.

Starting point is 02:00:04 The 100 wasn't really 100. Isn't there a little bit of a dynamic where you could wind up with like an anti-Google alliance? Maybe there's, you know, there's like tension between the industry and Google. This is like the foundational, like, myth of the AI industry and the AI. labs broadly, although they, of course, have fractured many, many times at this point. Yeah, I mean, you know, of course, there's always rivalries. You know, one might say people will gang up on Nvidia. You know, that's the occupational hazard of being the leader, right?

Starting point is 02:00:37 Yeah. I think they'll deal with it. I mean, I don't think it's a winner-takes-all-market, by the way. I think that, you know, there'll be space for others. Yeah, that makes sense. Last question from my side, then we'll let you go. Did you have any takeaways or ideas around the diffusion of physical AI and robotics? Did anything stand out?

Starting point is 02:01:00 Do you have a strong opinion there? Right now it feels like we've entered this sort of software singularity. But we just had Kayser from applied intuition on. We're talking with him about how autonomy and AI is diffusing through the physical world. But I'm curious if you had any takeaways. Yeah, I mean, look, I think that, you know, one thing sometimes people don't quite understand is that large language models and the transformer architecture that underpins them is super consequential for lots of applications, not just chat pots. And so robotics is being improved by this technology. And, you know, I fully expect to see a huge breakthrough, you know, over the next two or three years with the capability of robotics.

Starting point is 02:01:48 And so I think that's going to be the big story. I kind of agree with the guy from KSR you had before, that the movement of atoms is going to be affected as much as anything else. So that's part of why I don't think this is a bubble. I think, you know, the potential in, you know, this super powerful AI is enormous. Yeah. Well, thank you so much for coming and joining the show. It's a pleasure talking to you.

Starting point is 02:02:14 The book is The Infinity Machine. It's available everywhere. books are sold. Thank you so much. Fantastic cover too. Yeah, beautiful cover. Thank you for having me. We'll talk to you soon. Have a great rest of your week.

Starting point is 02:02:27 All right. Goodbye. Thank you guys. Let me tell you about fin.a.I. The number one AI agent for customer service, if you want AI to handle your customer support, go to fin.a.i. And we will kick off the Lambda lightning round. Let's see. Oh, look at this.

Starting point is 02:02:41 We got everything. This is amazing. Let's bring in Forrest. Forrest from Somos. Welcome to the stream. How are you doing? Hello, guys. How are you doing? We're doing great. First time in the show. Please introduce yourself.

Starting point is 02:02:55 What a setup here. This is a great setup. This looks fantastic. I come well armed with a bunch of nerdy stuff from the team, all the things we're building. No, I guess. Amazing. Yeah, break it down. Yeah, kick it off.

Starting point is 02:03:11 Let's see, where do I start? I'm Forrest. I'm a fancy plumber building infrastructure from scratch down here in Columbia to make internet way better and make compute and everything kind of work well in Latin American beyond. So very weird journey, but making the fastest internet in the world at the lowest cost is kind of a summary in a very short nutshell. Amazing. You have a lot of fans.

Starting point is 02:03:33 I got a bunch of texts from investors that were excited for you to come on. What were you doing before we get into so much? What were you doing before this? Dude, I came to Medellín when I was like 18 years old, basically just dropped. out of high school, it started building stuff, and ostensibly came to visit a friend for a couple of weeks, and that was eight years ago, and here I am. So I made websites.

Starting point is 02:03:56 I kind of took a very non-traditional path, and it led me to doing a bunch of weird stuff here. That's actually a non-traditional path. Normally, when somebody comes on and says they had a non-traditional path, it's like, you know, Stanford to a meta internship, a Google internship, a VC internship. But very, very cool.

Starting point is 02:04:15 What, yeah, breakdown, like, you know, you know, Somos, you're raising a series B today. Like, how long have you been at it? What initially, I can kind of guess what the initial inspiration might have been. You're building digital products, it sounds like, and we're probably frustrated with internet speeds. But what's the backstory? No, I came to Columbia in 2018. I got roped into helping people build this like blockchain incentivized, blah, blah, blah,

Starting point is 02:04:43 back when everything was going to be blockchain in like urban slums here in Medellene. And as those blockchain projects happened, everyone got bored really quickly, so they just left me with all the equipment. And I just kind of became fascinated by how do you build connectivity in slums and didn't speak any Spanish and know anything about telecom and just started tinkering. And the first couple of years were me like literally living in a slum here in Medellene, building internet, stringing stuff up in the middle of the street. And kind of bit by bit, I just became fascinated by the concept of like,

Starting point is 02:05:13 internet is the most basic thing for the modern world. And we just sort of assume that it's been solved. And really, we haven't done an engineering in the last, like, 30 years. It's the same underlying architecture that, like, John Malone was building in cable cowboy days. Yeah. Yeah. Every time I go travel to another country, I always look up, like, who the biggest industrialists are and who the richest people in the world. It's always the people that built, like, the railroads, the mines, the telecom, infrastructure, the Wi-Fi, the Internet, the power lines.

Starting point is 02:05:40 It's always, like the stuff that once you install it, it provides value. So, yeah, it sounds like it sounds like you're doing a lot. What is in your strike zone of things that you want Somos to take on versus where do you work with external partners? Like what is what is the kind of core path? This is kind of the insanity of Somos. So we literally do everything from like we interface with the submarine cables. We built like a nationwide backbone crisscrossing the country. We like make the Wi-Fi router.

Starting point is 02:06:06 So like the things that go inside of the thing here is all PCB. Oh, that's a Wi-Fi route. I thought that was just a pretty lamp. That's crazy. So this is literally the router that goes in customers home. So instead of being some like ugly, blinky box, it's like a beautiful lamp. That's super good. You're like, wait, does it have to be an ugly box?

Starting point is 02:06:23 No one thought of this? Dude, it's incredible. Like, the internet is like literally the most incredible machine humanity's ever built. And we're just relegated it to being this like ugly piece of infrastructure. And kind of our idea is like, what if it was dope? That's amazing. So, yeah, like how do you, like, how does the coverage map like spread out? Everyone's familiar with those like AT&T and Verizon coverage charts of like,

Starting point is 02:06:45 the map of America. Do you have to go city by city, block by block? Are there ways that you can, like, how do you actually scale out to reach an entire coverage area? So I literally have like a thousand plus employees cabling the streets. We have like linemen and installers and they're all worked directly for Somos. And this is kind of the insanity of what we're doing. And it's been a bit of a like slow flywheel to get ramping.

Starting point is 02:07:10 But then at the end of the day, you're building this actual moat because it turns out it's really hard to build new infrastructure from scratch. So we literally are cabling the entire city from scratch with a new type of fiber to connect people to faster, cheaper internet. Yeah, in what ways do you think it's easier to do in a place like Colombia than the United States and vice versa? Yeah, I think this is one of the interesting things is like the U.S. kind of looks archaic in comparison to some of the stuff we're building here. So like my base plan for customers like 12 bucks a month and is a gig and we're giving people 10 gig connections and soon 100 gig connections in their home.

Starting point is 02:07:45 So the kind of weird thing that has happened in the US is we sort of believe Comcast is sacred, so we don't let people go build new infrastructure. And we're almost, there's a world where it's like 10 years from now, we're like, shit, the US has like third world internet infrastructure. And what we thought of as the third world has infrastructure. Let's us do all these crazy things that AI is enabling

Starting point is 02:08:06 that you couldn't do before. So I think this was inversion happening kind of the same way as there were no landlines in Africa. We're kind of leapfrogging all the crappy old cable and just building internet as it was intended back in their ARPA days. That's amazing. How do you get people to move to Columbia to work on this? What's your pitch?

Starting point is 02:08:24 Not saying anything wrong with Columbia. It's just it's a long way away. It's a long flight. The time zone is not too bad, but... It's 75 degree other year round. We have awesome engineering. It's like San Francisco without the fog, and we get to just build it out of the hell you want.

Starting point is 02:08:41 It's kind of like cowboy Western technology, galtz-gouch in the middle of the jungle. That's amazing. Last question for me. I'm sure you got to ask this in all the VC pitches. How is Starlink rolling out? How is satellite internet fit into this? Is that a competitor?

Starting point is 02:08:58 Is that a compliment? A lot of people in America sort of have both. But how does that fit into the picture? I think the big takeaway here is I would sell your Comcast or Telephonic or TeleMex stock because I think what's happening is Starlink is a team. attacking lower density areas, moving stuff, mobile. Somos is basically building, think of Starlink for city. So we're building a pure play, just the best internet for dense urban environments.

Starting point is 02:09:24 And I think there's like a density threshold where below that Starlink will win. Above that, a thing like Somos will win. But realistically, like if I'm on level, if I'm on the third floor of a 15-story building in the heart of the city, like you're going to win on reliability, connectivity, speed, cost, all of that, right? Just base physics will be cheaper and way better and more reliable. Like even Elon will say this. He's like, Starlink isn't really for cities. It's for everywhere outside of that, right?

Starting point is 02:09:52 Okay. Yeah. So like basically unaffected by everything there because of physics. Always good news. Mutual friend, Zach asked me to, told me I should ask about how kind of AI is impacting bandwidth needs and how that that factors into the opportunity for you guys. Yeah, I think we're going to look back and say like, damn, the infrastructure we have currently is far underbuilt for the future of applications with AI. And one of the things that we are thinking a lot about in Somos is, what if you extend the data center to everyone's end home, all the crazy application that you can build on top of that, not only just speed, but reliability, redundancy, low latency.

Starting point is 02:10:29 I think there's a world where compute lives in data centers and we're streaming your OS. Think of like super Chromebooks to everybody and that that's a world where you make compute way cheaper and way better in a way that. historically wouldn't really be doable in traditional telecoms. And I think this is back to like, there's a world where Latam has orders of magnitude better compute than parts of the U.S. just simply because we rebuilt the telecom infrastructure from scratch. Wow. What other markets are on the roadmap?

Starting point is 02:10:56 Yeah, well, we're heading to Mexico in the very near future. And I don't know, there's some interesting neighbors of Columbia that are becoming open again, that it would be a new place to expand to from Colombia. so I think someone's Caracas might be a thing in the future. Before we hit the gong, another mutual friend, Aaron asked me to ask you about the high frontier. What's up with that? Yeah, I mean, I'm obsessed with this vision of the future as it used to be. And I think one of the things is stoked for me right now is like it feels like we're building awesome things like new ship factories and new infrastructure in the world that are like building a future as it used to be.

Starting point is 02:11:36 Like we used to think the future was going to be awesome. And we kind of got okay with a very boring, muddling kind of version of it. And it feels like we're now turning this wave of like, let's go build orbital space stations and the Lagrange points. Let's build fleets of autonomous vehicles. Let's build all these amazing things from scratch. So it's like build infrastructure, rebuild the world, make awesome things happen again. It's fantastic.

Starting point is 02:11:58 How much did you raise? We just raised 40 million in this round. There we go. Who came in? So Ribbitt led this. We had Bracket Capital and then USV, Kazick, and Y Combinator all kind of doubled down from the past. I love it. A great way. Great YC story too. Yeah. Fascinating company, fascinating industry. Just, yeah, I love it. Did you pop up to the West Coast for the raise or did you make everybody visit you?

Starting point is 02:12:33 It's a little bit of both. Like we get people to come down to Medellin and they're definitely not regretting when they come visit. So we have some fun adventures driving the countryside. I love it. Well, thank you so much for taking the time. Great to meet you for us. I'm sure we'll be back on soon. Have a great day. Cheers, guys. Goodbye. Let me tell you about Phantom Cash, fund your wall without exchanges or middlemen and spend with the phantom card. Our next guest is Dino from Serronic. He's in the restroom. Let's bring them in the TV being ultram. Dino, how are you doing? Good guys. How you doing? Thanks for having me on. Thanks so much for joining. Great to finally have you on. Yeah, give us the state of the union. What's going on with

Starting point is 02:13:08 Ceronic. Yeah, likewise. You may have seen today we announced the $1.75 billion financing round. So do we need to build some ships? What's going on? We've got to build some ships. We've got to build some ships. We're super excited for this. I mean, it is a true, true byproduct of the execution that the team has delivered on over the last, not just 12 months, but the last really 36 months since we started the company. I mean, our team is truly a plus. If you look at where we were just a year ago, we came off a $600 million financing round. What that let us go do is we opened our first shipyard.

Starting point is 02:13:51 We launched Marauder, which is 180 foot autonomous and unmanned ship. We then announced a multi-hundred million dollar project into that shipyard to scale production of Marauder. And then Coursera, which you see behind me right here, our small USB platforms, we've already taken production of those well in the into the thousands. So now as we look forward, what we're going to do over the next 12, 24, 36 months with this capital raise

Starting point is 02:14:20 is we're going to accelerate that. We're going to accelerate the production, accelerate the deliveries of our vessels to the U.S. and our allies around the world. We're going to launch new products. We're going to build new ships. And then we're going to go and build new shipyards. We're going to invest in the shipbuilding

Starting point is 02:14:35 industrial base in this country to the tune of billions of dollars. We're going to create thousands of jobs. jobs and ultimately we're gonna we're gonna unlock production rates that we haven't seen in this country since World War II and we're doing it in a very technology first software first approach. You mentioned USV is that unmanned surface vehicle? Unmanned surface vessel. Vessel, got it. And then so walking through the the use of boats used to transport people now we put equipment on them. How versatile are these vehicles? What are the different use cases? are some weapons platforms or some just ISR capabilities? Like, what is the range of utilities that the armed forces will get out of these USBs?

Starting point is 02:15:23 Extremely versatile. The whole point of the platforms we're building is actually for them to be modular by nature. Right? And actually, we actually try to change the acronym around a little bit. USBs like unmanned surface vessel. Yeah. You know, when you look in the past, it's really like a remote control platform. very similar to a predator drone.

Starting point is 02:15:44 We use ASV, autonomous surface vessel, because what we're building at CERONIC is not just one-to-one control, but it's true maritime autonomy to then go and deliver these platforms at scale and be able to control them at scale, meaning fleets of hundreds or thousands of vessels through the most advanced software on the planet for the maritime domain. And then when you're looking at the missions, the use cases that you mentioned, it really all just boils down to scale, persistence, and risk reduction.

Starting point is 02:16:15 Right? How do you operate large numbers of vessels? How do you do that continuously in what's becoming an increasingly dangerous maritime environment? And then how do you offer like real capability to commanders while keeping sailors out of harm's way? Keeping people safe is very, very critical and a key point to what we're building here. I don't want to diminish the work, but I'm curious about, how much of a challenge is it actually to create an autonomous surface vessel because it feels like when you're driving on the road there's so many random conditions and the car can flip over but boats it's a little bit safer I would feel like but am I missing something there

Starting point is 02:16:58 like the other boats that are trying to kill you okay okay maybe that's but I'm just thinking like a plane you know if it doesn't land perfectly it'll crash like boats you know they just kind of rock through the water, but there's obviously more to it. So what went into making it fully autonomous? There's a lot of, yeah. So the ocean is just a completely different environment altogether. So we deal with a lot of different challenges. Sure. One of the challenges that's really different from self-driving cars is, yes, there's a lot of complexities on the road. Yeah. But that singular car really only cares about how it gets to its end destination. It doesn't care about how the other hundred cars get to its end destination as well.

Starting point is 02:17:40 sure and how they're all working together collaboratively on a mission got oh and then you start throwing in six eight 10 foot seas high winds enemy environment some of the things that we're seeing now and like whether it's the black sea the middle east and we're anticipating in the indo-pacific like those are very very complex challenges that we're solving at seronic yeah uh what what goes into setting up a new shipyard do you have to kind of co-locate or existing shipyards, can you kind of stand something up, you know, totally independently? How does that, how does that work? Yeah, I mean, when you look at shipyards in the shipbuilding industrial base in this country,

Starting point is 02:18:22 it's really how do you bring on net new capacity? You're not really co-locating next to anything because a lot of that capacity has really atrophied over the last 30, 40, 50 years. So what we're focused on is building new shipyards and then building the ecosystem and the infrastructure to support that as well through partnerships and vendor relationships. But one of our one of our main projects and one of the things that a large part of this capital is going to go towards is Port Alpha, right? We have a shipyard in Franklin, Louisiana, mentioned that we're investing hundreds of millions of dollars in that yard, but we're looking at a brand new shipyard, building this from the ground up, completely greenfield, investing billions of dollars

Starting point is 02:19:04 to 10x the size of our existing yard. to bring on new scale, new capacity, and rebuild the shipbuilding industrial base from the ground up. That's what's needed, because if you go around the country right now, you go to places which used to be shipyards, and you'll see apartments and condominiums

Starting point is 02:19:24 that are called naval yards. That's not just the name they came up with. It actually used to be a shipyard. So what we're doing now is we're investing in the shipyards of the future, again, to produce out a scale that we haven't seen since World War II. What's the best way to get a job at Serronic?

Starting point is 02:19:41 You can apply on our website. I mean, we are hiring. We are growing. I mentioned how amazing our team is. What we're doing is absolutely critical for the country. The team comes in every single day. The work they're doing is changing the world. And so if you're a top engineer or looking to get into the defense tech space, please, please apply.

Starting point is 02:20:01 Everything we're doing is absolutely critical. We grew the team from 200 to 30. 1,300 people over the last 12 months. And that's, that's only the beginning, guys. That's amazing. Well, thank you so much for coming up and breaking it down. Have a great rest of your down. Yeah, incredible progress. The chat says just put the S1 in the SEC mailbox, you know. We'll talk to you soon. Good to see you. Thanks, guys. Look forward to following up. Let me tell you about OXTA. Octa helps you assign every AI agent a trusted identity so you get the power of AI without the risk. Secure every agent, secure any agent.

Starting point is 02:20:36 with Octa. And our next guest is already in the stream waiting room. We got Will Ahmed from Whoop. Whoop. He's back. How you doing? Good to see you again. Welcome back. Hey, guys. Thanks for having me. Give us the update. What happened? How you doing? Things are good, thank you. We announced a round of financing today, our series G, $575 million round. So, oh, hey. Yes. There we got. Thank you. Is this the capital that you finally need to make a bust down whoop? Diamonds from the factory. That's what I'm looking for. Can you do anything for me?

Starting point is 02:21:13 You know, we do. We do have some premium offerings in the mix that are going to be just right for you, actually. Perfect. Perfect. Very happy with product development. Jorny wants a bust out. No, no, seriously, give me the updates. What's changed?

Starting point is 02:21:29 Where do you want the product to go? And yeah, I am interested to know. Are more collaborations in the works? Do you see that as an important point? Or are you just focused on more and more channel partners, more and more distribution, more growing because the product's pretty dialed at this point? Well, look, it's been an extraordinary 12 months for the business. You know, we ended 2025 with over 100% year-over-year growth, you know,

Starting point is 02:21:56 $1.1 billion in bookings run rate to end the year. Our membership is growing around the world. We're operating in 60 markets. We've got WOOP members in over 200 countries. We've launched medical grade technology now coming out with blood tests around the world. And so WOOP's really become this broad-based health platform. And you can see that in the financing announcement today. You know, we've got the history of WOOP with the world-class athletes.

Starting point is 02:22:25 We've added now. LeBron James is a new Woop investor. We've got Christiana Ronaldo on the cap table, Virgil Van Dyck, Matthew Vanderpull, some of the world's very best athletes, really from every sport, are now on the whoop cap table. And then in addition to that, we've got a bunch of great existing investors continuing to support the company, collaborative fund, IVP, Foundry Group, and more. And then we've brought in some sovereign wealth funds from the G.C. Proud to have Mubadala and QIA and 2.0.

Starting point is 02:23:05 So really some of the biggest funds in the world that are, I think, phenomenal long-term partners. And then lastly, to the point about health, you know, we've added the Mayo Clinic is an investor in WOOP, one of the premier health institutions. There we go. That's a niche. That's a rare Pokemon, adventure world. I haven't heard of them on a capital. I'm not ripping a lot of seed checks at YC Demo Day. Yeah, they haven't done a lot of investing, but we see a ton of synergies from a research and medical capability standpoint.

Starting point is 02:23:36 And then we also have added Abbott as an investor and, you know, really one of the best medical device makers also in the world. So it's a phenomenal mix of investors. And I think we've been able to achieve this because of the remarkable growth that we're seeing as a company. And I think also just the tailwinds around health and longevity. How do you think your marketing mix will change over the next few years? Because I'm seeing $575 million, LeBron James, Christiana Ronaldo. That has like crazy Super Bowl ad written all over it. At the same time, your tech native, I could imagine going way further into AI generated,

Starting point is 02:24:16 personalized ads, pushing the performance marketing further. Like, what appeals to you? How do you think you'll change? What will stay the same? What will change over the next few years from a marketing? perspective. Well, we never want to lose sight of the fact that we started in sports and we've built this aspirational performance lifestyle brand. And so that'll really be at the core still of a lot of what we do for WOOP. But we also now have a product that, you know, can detect whether you have

Starting point is 02:24:44 AFIB and tell you your blood pressure every morning and help you do blood tests. So it's just a much broader health platform than it's ever been before. And our marketing needs to reflect that. You know, one of the areas I would say of maybe not weakness, but opportunity for whoop is brand awareness. You know, we don't have massive brand awareness around the world. And so this capital is going to give us the gunpowder to really grow broadly internationally. And so you're going to be seeing a lot of whoop wherever you consume content. Super Bowl ad incoming. Yeah, I mean, if you want to reach me specifically, maybe a partnership with an athlete like Johnny Knoxville might work.

Starting point is 02:25:24 It just might make sense. We'll do a whoop live heart rate on some of the stunts. Stunts. I think that would do the trick. I'm curious, like, how, whoop, like, how do you guys think about improving accuracy at this point? Like, I'm assuming, like, so much progress has been made over the last however many years, but there's still always incremental progress. You can always be more accurate.

Starting point is 02:25:56 How do you think about that? Is that still like a top priority? Or are there other, is it accurate enough at this point that there's better things you can focus, you know, the core energy of the team on? I mean, I think big picture, we want the product to be getting constantly smaller and smarter. You know, we want it to be an aspirational product in the sense that it's something cool that you wear on your wrist. or we want it to be something that disappears throughout your body and can essentially be invisible. And so however you can gather this data super accurately, have the data sets grow in nature, more sensing, more capabilities, more medical approvals, the better.

Starting point is 02:26:41 And I think that's going to continue to expand our TAM. I think it's going to continue to deliver deeper insights for our members. So we're going to be leaning in pretty heavily on research and development. You're going to see a lot of very powerful sensing. coming from WOOP in the years to come. How is the peptide boom affecting Woop? Well, I think the underlying reason for the peptide boom is that people want to take more control of their own health.

Starting point is 02:27:09 And they're sort of generally frustrated with the tools that they've had to improve their health. And so that leads in different directions. Peptides being part of it, supplements being part of it, concierge doctors being part of it, AI health coaching being part of it. But broadly speaking, it's, I think, good for Woop that people want to take more control of their health. And 10 years ago, I would talk about health monitoring and people would say, well, that sounds like something niche for athletes. And now, you know, everywhere I go, people want to talk about how they can improve their sleep or improve their VO2 max or what is heart rate variability.

Starting point is 02:27:48 So there's just clearly been a cultural shift to care a lot about your health. And, you know, longevity has become one of the most common reasons that people use the product. Our health span score, the whoop age score, has become the most screenshoted page in the Woop app. So clearly you've got people who want to show off how old they are or, you know, who want some counseling for how old they might be. Yeah. Yeah, that makes a lot of sense. Yeah, there's an interesting dynamic with the various health platforms where there's like kind of an incentive, there's like a weird incentive to like, you know, measure. say somebody's, you know, their chronological age versus their biological age make it, like, lower.

Starting point is 02:28:32 Yeah, yeah. People are more likely to share. It's like, I've seen, I've seen some people have, you know, come in and say, like, well, my biological age is 19. I did one test that said I had the mind of a five-year-old. It said, it was testing my brain health and it said that I had the... Is that good or bad? It's not...

Starting point is 02:28:50 It's extremely young. I'm way over five. So I assume it's good. I think we've built the most credible biological age metric. First of all, we did it in partnership with the Leading Longevity Institute out of California and then the Buck Institute. And then we show you in great granularity each of your biometrics and what's improving it and what's not and by how much. So here's a trivia question for you. What percentage of people on whoop do you think have a younger whoop age?

Starting point is 02:29:23 Oh, interesting. I mean, if it was perfect, it would be 50-50, I would think. 70% because people that use whoop are much more likely to be healthy. Okay. So let's go with 70. What is it? It's 55%. But what that means is 45% are older on Woost. You know, great sound. They're early in their loop journey. You guys have done a lot. This whole show is really dialed in. No, so 45% are, uh, uh, 4,000.

Starting point is 02:29:50 Yeah. So, you know, but that shows that, like, it's going to push you. Yeah. Yeah. Yeah. And I, and I only, I only brought that up originally because I've seen some of these come out and I'm like, okay, there's zero shot. This person's biological age is lower than their chronological age. Based on the life we live. Not every platform, you know, platforms are just kind of every platform is going to run. their own kind of algorithm to determine that and not necessarily working with the Buck Institute. Yeah, exactly. Well, very cool. Fantastic progress. Great to get the update. Congratulations. Congratulations. Congratulations. I feel like just in the last year, like the world has woken up to this kind of category. Yeah. And your guys' progress is a testament. And I still

Starting point is 02:30:41 think it's, I still think it's very early. It must be fun to walk down the street for you. And, you know, someplace like LA. Oh, yeah, you probably see them everywhere. And, you know, I'm sure it's like every 10th person as a whoop band on, but that means there's nine, nine or so. Yeah, it is, it is a trip seeing, seeing whoop in the world. And, you know, for people who decide to take the hard path of building hardware, it's an amazingly rewarding feeling when you see a physical product that your team's built in the world. So I will say that's a, that's a very gratifying thing. But you guys, you guys owe me a question here. You haven't asked me. What is it? What's the question? Aren't you going to ask me if the job's done?

Starting point is 02:31:19 Oh, yeah. Is the job finished? Job's not done, guys. We got to keep going. Thank you. Thank you for that. Great stuff. Thanks. I appreciate you guys.

Starting point is 02:31:34 Keep it up. We'll see you at nicey soon, I'm sure. Get ready. The chat's going to be your strongest supporters. Thank you so much for taking the time to come chat with us. We'll talk to you, say, well. Have a great one. Goodbye.

Starting point is 02:31:47 Let me tell you about MongoDB. What's the only thing faster than the AI market? Your business on MongoDB. Don't just build AI, own the data platform that powers it. Continuing our lightning round. You know who we got? The CEO of Public.com. Yannick, how are you doing?

Starting point is 02:32:05 Hey, guys. I'm doing well. How are you? We're doing fantastic. Look at that stuff in the background there. I know. Do you recognize any of this stuff? Oh, yeah.

Starting point is 02:32:12 Yeah, you got the whole head to toe. Head to toe. I don't recognize what Jordy is wearing. I don't think. This is new. This is new. This is the new polo. You're right there.

Starting point is 02:32:21 Top left. You got lead left. You got lead left. There's a room on the wall. Plenty of room on the walls. Anyway, enough about our merch. Let's talk about your business. Walk us through the launch today.

Starting point is 02:32:32 Yeah, so today we launched AI agents for investing. Yes. The easiest, safest way to put AI agents to work directly inside your portfolio. Yeah. And the way it works is pretty simple. There's now an agents tab directly within the public app. You chat with an AI to set up of agents that monitor markets, move money around, and even execute trades for you all within

Starting point is 02:32:55 the app, right? So there's nothing to install from a security standpoint. Obviously, everything stays in a safe, controlled environment because it's within the bridge. Can I install Axios? No, do not do that. That is such a niche joke. Everyone's going to think you're talking about the publication. Yeah, exactly. No, but I mean, it's been really fun. I have a bunch of agents running now on my account. It's been really awesome to see how it's changed my behavior as an investor, right? So, John, relax. I like the sound of that. I knew you're going to do that. We got a little John in the studio. No, so, so, so, uh, make, makes total sense. What, like, if people are, like, already signed up, which they should be how, what, what, what, what, what's the first thing that,

Starting point is 02:33:39 that, that they should try to, like, set up or experiment with? Like, what, what was your first few agents that you've set up and like continue to keep running because I'm assuming you can effectively like run them you can retire them at different points exactly exactly the first one I set up was one that checks the oil prices before the market open and buys protective put options every day as a hedge sure if there's a spike in those I call it the I'm tired of seeing red due to war agent and so today that didn't fire thank God you know I have another one that just looks at my bank accounts and automatically sweeps any cash in excess of a certain amount into my bond portfolio. So I'm always yield maxing.

Starting point is 02:34:21 You want to be yield maxing always, especially while rates are still high. Yeah, that makes sense. And then I got some more advanced stuff. Like I got one that scans the market for opportunities to write cover calls. Okay. Across my top position. So if there's a low risk opportunity to make like 20 grand a month selling options premiums, I instructed to just go ahead and place those orders.

Starting point is 02:34:42 And so that just rolls. every time, all the time. And I don't have to think about it. That exact strategy was the first thing a private wealth manager ever pitched me in my career like a decade ago. They were like I, and they had like a guy that did it.

Starting point is 02:34:55 And you had to have a lot of money to like access that. And there were minimums and stuff. You should probably check on that guy. After today's launch. But, so, so I, there are obviously like incredibly advanced things

Starting point is 02:35:06 that you can do with these agents in, in the market. I'm also interested in just driving behavior change. Because a lot of, folks that I know are earlier in their career, they don't want to necessarily take a ton of risk. The biggest lever on their financial future will just be seamlessly funneling money from their paychecks into something as simple as VTI, and then they can do something more advanced down the road. But what does it look like in terms of the best practices or best functionality for

Starting point is 02:35:36 just creating a set it and forget it? I want to make sure that every time I get paid, money's flowing into the market. How easy it? is that these days? Well, I think with agents, that becomes really, really simple, right? I think this is sort of the whole point. You know, the stock market has always been about manually entering orders, right? Like, you do all this work, and eventually you end up manually being like, buy 200 shares of Apple at this price.

Starting point is 02:36:00 Yeah. I think that user interface is now shifting to something like, increase my position if valuations compress 15% from here, you know, and it stays within my defined risk tolerances and so And so I think it changes how people think about and manage their portfolios in a pretty profound way. And we do see it as a user interface shift. Like, you know, the interesting thing about this industry is every technology kind of had their model of brokerage, right? Like we started on the horn and then the dawn of the internet gave us the discount broker with mobile came the Neo broker. And I think now with AI, it's the era of the agenic brokerage. But what's uniquely

Starting point is 02:36:39 interesting about this shift is every previous shift was about. streamlining the process and reducing the responsibility set of the broker, you know, to basically just trade execution ultimately. But it actually used to be much more full service. To Jordy's point, there used to be a guy. I used to call you, used to pitch all these kind of ideas, risk, you know, trade ideas, etc. I think with the identical brokerage model, you're reversing back to that.

Starting point is 02:37:04 And it's much more full service than obviously any human service could ever be because this thing can like write an algorithmic trading script for you in 10 seconds. They can do taxiles harvest. They can instantly analyze risk. Sure. And so it's a shift back to a world where the brokerage plays a much larger role than just trade execution. It sort of goes into the realm of maybe a quant and a financial advisor. And that's what we're excited about the brokerage playing a much bigger role through essentially agentic AI.

Starting point is 02:37:32 George. Can it pull in external data sources yet? I'm thinking like fear and greed index. Like should I? Could I set something up where it's like, if you have like max fear that you want to buy on days when the. Yeah, yeah, yeah, yeah, yeah, a fee index is high. But that might not be an actual, like, instrument in that you can buy and sell directly. Yep, 100%.

Starting point is 02:37:56 Unemployment data, CPI, Fed cards. Like one that people have been kicking around today is, you know, whenever there's a Fed card, move money, obviously out of my high-yield cash account on public, put it to work into high-growth tech. Yep. We like the sound of that. All right. That makes sense. There we go. And so there's a lot of those.

Starting point is 02:38:16 CPI, like the Fear and Greed one was requested today. I think that's coming in the next couple of days. And so really it's about getting all that into this natural language interface and just letting people kind of instruct AI to do this on their behalf. Last question for me about AI on the platform. What have you, what are the capabilities? What have you learned about users educating themselves? about various financial instruments within the public ecosystem.

Starting point is 02:38:46 You know, okay, I see a company, you're going to surface price to earnings ratio, market cap, the usual stuff. But there's so much more that you can ask in LLM these days about what does a company actually do? What is their strategy? What's the history of this company? Do I, what's the founder? Like these things are perfect for LLMs and you can vend those in. But what are users actually using what's adoption been like? What have the learnings been?

Starting point is 02:39:11 Yeah, I mean, I think one of the core tasks and application layer is to sort of figure out, obviously, what are users want to achieve? Yeah. And then which model and kind of harness is best suited to achieve that purpose? Sure. But then also focus on, like, what are we uniquely able to deliver, right? So we know what you own. We know what you used to own.

Starting point is 02:39:32 Yeah. We know what your risk tolerance is. By the way, we also know the difference between what that actually is and what you said it was when it's signed, when you signed up. Yeah. And we have real-time data feeds of everything, right? And so I think as a product builder, those are like some of the situations where you can really create a magic moment that general purpose, LLMs, can. And I think a lot of that comes because we just have a lot of that kind of history about how people like to invest, what questions they've asked to your point in the past about the PE ratio or what the founders like, et cetera.

Starting point is 02:40:04 Because we've been basically running a research system since 2023. And we're only a six-year-old company. So it's already for sort of like half the time that we've been live. And so we've been able to gather a lot of data for the last three years that we can now kind of repurpose into this. What's your theory right now? It's obviously day one. But do you think in the future we'll get more volatility because you have like financial institutions that are effectively using like agents or algorithms to do trading? and then you also have retail.

Starting point is 02:40:37 So when you get like a new CPI print, you know, you have, you know, even, you know, additional trading activity off of these single events. Like, do you think this is something in the future that everyone will effectively have like a handful of agents running just naturally in the product? And then some people, you know, be like, you know,

Starting point is 02:40:56 maybe pro sumers, people that are more into it will have, you know, many or at some point is everyone, you know, at what point do, is it like, you know, old, fashion to be just like, you know, buying a stock yourself even with a button. Totally. I actually think we will look back at like tables and buy buttons and feel that's a little antique, maybe already 12 months from now. But I think the effect is things will get priced in faster, for sure.

Starting point is 02:41:23 On the institutional side, they've, you know, they've used some version of AI for the longest time, right? But then at the same time, retail have gone from being like 5 to 25% of the market. And on the retail side, folks haven't been. been as fast to react always, right? They haven't been the discipline. They're not necessarily glued to the screen 24-7, and so, you know, they can't always react as quickly as they want to, and agents obviously change that, right? And so I do think that there might be, I mean, it's a little bit like, whether it's crypto, prediction markets, there's always a little bit more

Starting point is 02:41:55 of sort of an alpha opportunity or an ARP opportunity in the early, early days. And then over time, it becomes more mainstream and that kind of fades away and I would suspect that this follows something like a similar pattern at least. Yeah, I've just been thinking about it because the content on X is primarily user generated at least the big accounts. It means that an event happens in the real world.

Starting point is 02:42:18 It gets reported on or it pops up on a website or you get a newswire and then a human takes that and puts it on X and then the straight, even the majority of retail volume is like flowing off of like that human seeing the news. posting it and then you get this sort of trading activity but in a perfect world you see news and then you go to your broker and the right trade has already been made on your behalf and anybody that's not adopting this will just be like well i i missed kind of i miss opportunity unless you want to

Starting point is 02:42:50 get out entirely totally speaking of x a fun one is uh that was front of day was if dj t says bye just buy that's actually That's actually really smart. I think that's probably backtests very well. The backtests extremely well. What a crazy timeline we are in. Well, thank you so much for coming on and breaking it down for us. Great to see you.

Starting point is 02:43:15 I miss you. Let's be sure to hang out. Let's hang soon. We will. Yeah. All right. Bye. Cheers.

Starting point is 02:43:21 See you. Ciao. Let me tell you about Century. Century shows developers what's broken and helps them fix it fast. That's why 150,000 organizations use it to keep their apps working. And without further ado, we have Ryan from Crosby. How you doing, Ryan?

Starting point is 02:43:37 Welcome back. Hey, guys. Good to see you again. Dude, you're on here like every week. It's getting ridiculous. Yeah, it's getting a bit much. Let me guess. Let's schedule the next one.

Starting point is 02:43:45 You should just bundle all the fundraisers together into like a series alphabet. Then you just do it all over once. But I never get to see you guys. It is more strategic to break them up. But tell us what happened. How much did you raise? What's going on? We have two announcements.

Starting point is 02:44:00 The first announcement is we've raised $60 million. led by Lux. The series B. Our second announcement. Thank you. The second announcement is we did some math last month, and we have now closed contract worth over a billion dollars for our clients. It's a big milestone for us.

Starting point is 02:44:17 Okay, a billion dollars for the client. Very cool. That's good. Is there a power line there? Was there like one sneaky $950 million deal? Did you get one percent of this new open AI round in there? Somebody was like, I'll get it really one clause. And you're like, no.

Starting point is 02:44:32 It sounds like there's a lot of lawyers using it. That's right. I mean, these are small deals, so it's a lot of velocity. I think definitely my corporate law friends are like, that's like one deal for me. That's not interesting. But for us, that's a big number. That makes sense. So it's a really good milestone. Yeah. So yeah, yeah, take us through, I mean, it sounds like like the shape of the work that is being augmented by Crosby these days. Yeah. So, you know, we're about a year and a half into it. We announced our seed around 230 days ago. We do commercial agreements. These are the sales agreements. MSAs, NDAs, VPAs for like fast-growing AI companies. Now we're branching out. But since the beginning, we've been a law firm. So we have about 30 lawyers here who I'll give a shout out to are just the last day of the quarter. They're working so hard for our clients getting the deals closed.

Starting point is 02:45:20 And we close deals fast like in a couple hours. And so this idea has just taken off with a lot of tech companies now and now even bigger clients who just want to close faster. How have you been processing? you're kind of, I would say, very tapped into how well the models work in different roles. I'm curious your view on how application layer legal AI companies will do compared to just the labs themselves, right? I feel like every other day on X, somebody says, wait, this LLM seems to be doing just as much as, you know, this application layer company. you guys are using all the models internally for your own internal tools.

Starting point is 02:46:07 But how are you processing kind of what feels like in the same way we saw with CodeGen where you have application layer companies and foundation model companies and then you have foundation models with their own applications. I'm assuming we'll see that in legal, but how have you been kind of processing it? So, I mean, that is the question we have to ask ourselves every day. we think that code generation more or less is kind of like a year and a half ahead of the sort of non-self-verifiable domains

Starting point is 02:46:38 so anything that's not like math or code and law is one of those but it's a huge service area and our sort of like insight a couple years ago was let's not think about these sort of like AI co-pilots that are kind of like you need to build up what cursor was a year and a half ago when you kind of hit tab to autocomplete but these long-form agents with bigger context

Starting point is 02:46:56 that could do a full job end to end. And if you have agents, that can do entire swaths of legal work, then the best thing you should do is start a law firm because you're selling work to clients, not fractions of work or kind of helping them along. And in truth, we were ahead of the models, and so we were selling something that like we weren't able to fully automate.

Starting point is 02:47:13 And as the models are progressing, we're seeing more and more of a compounding advantage as we have more and more contracts that we're processing. We have more and more lawyers that were able to help us, you know, tune judges and, you know, like create better agents. And so we're able to just do end-to-end work in a way that like if you're just selling a legal, you know, co-pilot, I think you're going to face a lot of competition just from the models with no customization.

Starting point is 02:47:36 Yep. Sorry. Wild. John's back. Yeah, wild moment. What, I'm assuming you'll also face competition from clients that are just like, hey, we can, should we, should we have an in-house lawyer that we can, you know, speed up? But everybody's competing with everyone.

Starting point is 02:47:58 but yeah. How are you tracking the legal education market? I've seen it, it seems very hard to predict for me. Like there was this weird spike. I want to say like it was maybe post-chatGAPT where there were like more people signing up for a law school. And that was like sort of contrarian based on the model capabilities

Starting point is 02:48:18 like the AISF discourse, but maybe it makes more sense. Like are you tracking that data? And then are you tracking like how legal education is changing? I imagine that using AI tools already happening in middle school for a lot of people, high school, definitely college, definitely law school. How will that all trace through and how closely are you following it? I mean, I think every industry is asking themselves, like,

Starting point is 02:48:45 how do people get the entry-level jobs to learn those skills and become really good and senior and get leveraged by agents? I went to law school of Stanford. I'm talking to a lot of professors there who are struggling with this question. I think our insight for now, like the stat we found recently, is that the top 100 law firms last year made a little under $70 billion and just profit, just in 2025.

Starting point is 02:49:04 That's just paid out to their partners. That's just salary. And that's bigger than... Good year. It's so good to do. And that was more money than Google spent on all their R&D. And so like our insight was... Mogged.

Starting point is 02:49:19 Which is great. So like, if we could just put some fraction of the profits law firms are making into building better tools and experiences for lawyers and for their clients. I actually think the legal industry gets a lot bigger. And so it's like for a person in law school today, it's a good time to be thinking, like, how can I just build better stuff? And that's just a new way of lawyers thinking.

Starting point is 02:49:37 Okay, that's one way to put the profits to work. Let me pitch you another way. If I'm a partner at a law firm, and I see that, yes, agents can do the work of the associates that I would be hiring. Yeah. Maybe I, you know, a contrarian in me wants to still hire associates just for the mentorship and, uh, and building like the pipeline of partners that will do more human work, more deals work, more interpersonal relationship work. But I know that if I don't start buying and paying for that service right now, even if I'm getting less margin on it loosely, because I'm paying an associate a bunch of money and it's work that an AI agent like sort of could do. and maybe they're a little bit more free.

Starting point is 02:50:22 I'm actually incentivized to figure out how to accelerate them faster in their career, have them start working on larger, stickier deals that AI can't necessarily navigate just yet. Yeah, I mean, I buy the argument. Like, I think that there's two jobs for lawyers really to focus out right now. One is just doing client-facing work

Starting point is 02:50:41 and being really good at being, like, you know, talking to people and understanding what their points of view are and not being buried in the sort of paperwork like their typical associate. And the other is being, able to explain reasonably well to an engineer or a researcher what it is you're doing and what you're thinking about and all the subtleties of context. And those two things, I think, are both things

Starting point is 02:50:59 that if you're not hiring enough lawyers, you can't do well and you can't build better legal technology and experiences. And so I think we're feeling this and every law firm is something like, you just need people to be really thoughtful about doing both those jobs. Yeah. Are you guys fine-tuning any models, you know, based on fine-tuning like open-source models or is that not even, you know, I've seen like Finn and Notion have had some success with this. Is that even a good use of time right now? Because I'm assuming your guys's actual inference costs or not that high relative to what you can charge clients, even if you're using the frontier models. But how are you thinking about that? I think, again, if we just look

Starting point is 02:51:38 at cogeneration as like the blueprint for the future, you see like a lot of the cogen companies got a lot of lift from just like, you know, the main, you know, three big models. And over time, you have to start fine-tuning your models as you get scale, as you get data, and as you need a more competitive edge. So we're not there yet. We have a lot of lift from just getting the right context to models, building the right agent flows, like just doing some reinforcement learning on like basically we work with really, you know, open AI anthropic in Google's models. But yeah, in a year and a half, as you get really specialized in use cases of law, I'm sure like we're going that direction. And part of the reason for this funding and doing it so quickly is to start investing in a research

Starting point is 02:52:16 team that can kind of push the boundaries there. That's very exciting. Well, congratulations in the funding round. I'm sure we'll see you. We'll just book it now. You just tell us. Same time next month. Thank you, gentlemen. We'll talk to you soon. Have a great day. Thanks, guys. Let me tell you about Shopify. Shopify is the commerce platform that grows with your business and lets you sell in seconds online, in store, on mobile, on social, on marketplaces, and now with AI agents. And without further ado, we have Chris you. And also, how are you doing, Chris? Chris? Thank you, so much time. Yeah, thanks for having me.

Starting point is 02:52:50 Welcome to the show. Since this is your first time, please introduce yourself. Yeah, my name is Chris You, and I'm the co-founder and president of also. Okay, break it down for us. What is also, give us some of the corporate lineage, the strategy, the product, just sort of everything. Yeah, so actually before 2020, RGA and I met, and we immediately hit it off this one topic. And so that turned into me joining Ribian at the time. Cool.

Starting point is 02:53:15 with the explicit mission to create a startup within a startup. The entire thesis that we had, and this has turned into also with a spin-out last year, is that if you look at the vast majority of trips that happen for the moon of people and goods around the world, they happen in smaller than car things. But nearly none of them have been electrified yet. And so it's really taken the Rivian or Tesla playbook and applying it to these smaller form factors. Okay. Smaller form factors, that means everything from hoverboard to a horse and carriage. What are we thinking?

Starting point is 02:53:46 We're focusing on wheels first, but yeah. Okay. But yeah, yeah, narrow down the product for me, the go-to-market, the quad and the pedal-assisted electric bike. Are there timelines, shapes, sizes, ranges? Like, how do you think about narrowing down the product set? Because it is a really wide and diverse category. Totally. Yeah, so we think of it as, in a way, two phases of the business.

Starting point is 02:54:15 Phase one of the business is how do we create a vertically integrated software-defined EV platform, but optimized for small-form factors. And we've applied that to our first products. We call them EVs that you can pedal. And we announced those back in October. So one is a consumer e-bike. And the other is a pedal quad, which we partnered with Amazon to deploy soon. That's really exciting.

Starting point is 02:54:37 Cool. But if you look globally, again, today things move around in things like two-wheelerers, like scooters, bodobotas, tuck-tucks, microcars. microcars, K trucks. There's just these rich, diverse set of form factors. And again, none of them have been electrified, and all of them are ripe for a really kind of tech forward platform, which is what we're building.

Starting point is 02:54:57 But importantly, today we announced a partnership with DoorDash, and that kind of underpins phase two of the business, which is... Very good. Thank you. So if you look at the world becoming more and more autonomous, and even as that happens, some fundamental constraints don't change, meaning these trips are all happening in dense urban suburban environments.

Starting point is 02:55:17 Congestion is always going to be an issue. Cost per mile is always going to be a factor. And so we believe really strongly that even in a fully autonomous, autonomous world, small form factors make sense for a lot of these trips. And that's really what this partnership is about. Talk to me about, I mean, I love RJ. Rivian is an incredible company. Obviously, a younger company in many ways than other EV makers. that might be more vertically integrated.

Starting point is 02:55:45 So I'm wondering, like, how much is it that you're taking the supply chain knowledge, the expertise, the best practices, the connections, and setting up sort of an entirely new supply chain that's distinct, versus you're just going to be able to buy stuff from Ravian or license it, or there's going to be more of a business relationship other than just funding? It's all of the above we, RJ and I talk about us as kind of like sibling companies, if you will. So I think, I mean, there's a few aspects.

Starting point is 02:56:12 One is we share the latest and greatest from a technical architecture standpoint. So if you look at how also vehicles are built, they're very, very similar in terms of how what Rivian is built. There are some commodities that are shared. So battery cells, our first products actually use the same cell that are in Rivian R1s, and that helps a lot from a scale standpoint. But there are other areas where we are taking a decidedly different path because our products are different from a car truck or SUV.

Starting point is 02:56:40 So supply chain that you mentioned, that's actually one of them. We are fully engineered in-house, but we partner with contract manufacturers across the world to be able to do assembly. And that's right for smaller-scale products. Yeah. And with cars, you almost always want to manufacture them where they're going. Like, that's why even like the Japanese car makers have facilities in America or Mexico because you just would drive the car as opposed to put it on. That's exactly right. If you look at a car, I mean, the size of tools necessary.

Starting point is 02:57:08 Yeah, everything. Custom they are, tariffs. Like they all have to like you have to have your own factory in region. Yep. But if you look at any product south of a car, almost all of them are built with this contract manufacturing model. Okay, talk about the name and the brand. Rivian has those delightful headlights.

Starting point is 02:57:24 A lot of different interesting brand decisions around Rivian. What are you taking? What are you thinking? And where does the name come from? That's so great. I love it. We naming something is so hard. And so RJ and I battled quite a bit with,

Starting point is 02:57:39 this, but when we landed on this one, we knew it was the one because if you look at transportation, it's always been so singular narrative. It's like it's just cars or it's just not cars. And for us, the approach is like whether it's a commercial enterprise or a consumer, it's all above, most likely, meaning that I want to use my R1 to go on a long weekend trip, but my school drop off with my kid, it's a pain in the butt to sit in the car line and something smaller probably it makes more sense. And so the transformation of electrification of transportation is also. It requires all the above in a way. And on kind of like how we present ourselves from a brand, you know, one analogy that RJ and I really love and use often is it's kind of like we're

Starting point is 02:58:25 two characters in the Marvel universe, if you will. So it's like we have the same mission, but we can have very different personalities. And so also has an opportunity to be maybe in a way really expressive and take a little bit more liberties, which you're starting to see in some of our products than a more grown-up vehicle brand may need to be. Okay. How do you think about competition with Chinese manufacturers? Rivians had the benefit of not having to compete with all the Chinese manufacturers

Starting point is 02:58:52 in the U.S. I imagine micromobility is not going to be having the same kind of export restrictions. you know, how do you think about that threat? Assuming that, you know, there's Chinese companies out there that for one reason or another will be able to like sell out a loss for some amount of time. Yeah, the DJAI story, basically. Yep. That's a great question.

Starting point is 02:59:19 I think there's a couple of ways to think about it. Increasingly as you get to the larger form factors in our portfolio, when certainly as we get into autonomy, I think a lot of the similar factors that we're seeing in the automotive world in terms of, of the natural firewalls that are happening will exist in our space to some extent as well. But just to back up, I think one of the things that gets lost is there are a tremendous number of products in this kind of like small mobility or micromobility space that are coming out of China for sure.

Starting point is 02:59:50 But I think it's without debate that the vast majority of these products are commodity, like relatively low quality, white label type products. That being said, there are a small handful that are really, really great products. and using the latest and greatest tech. And if you look at take apart one of those products, and you take apart one of our products architecturally and from a technology capability standpoint, they're actually more of the same than not.

Starting point is 03:00:10 And I would say also is probably one of the only brands outside of China that you could say that of within this space. And so just purely from a product feature quality and technical capability standpoint, we feel like we're very, very competitive. Okay, product pitch. The Rivian R1T has a gear tunnel. It fits a snowboard.

Starting point is 03:00:30 Electric longboard with, a handle that flips up like a giant razor scooter that fits perfectly in the gear tunnel. Am I on to something? I love it. That's not the first time we've heard that one. Oh, really? Okay. The gear tunnel, it just does feel like such a unique feature and it just demands some

Starting point is 03:00:49 bespoke thing that fits in there. You know, you want like a big speaker, Bluetooth speaker that fits in there, like barbecue or something. It just, I want an ecosystem around the gear tunnel. Who knows how viable that is. Anyway, very fun. Jordy anything else very cool thank you so much I'm on the website right now I'm I'm shopping you're shopping I'm shopping I'll hook you up just let us know we'll be very

Starting point is 03:01:10 excited to ride these around we've been doing we've been doing some uh office chair racing in the studio this is apparently a whole that's what I want I want an electric office chair oh there you go we have well we have in-house vertically integrated motors and we can power we can soup those up yeah so I can just add up adjust me to the left one inch. Yeah, just a little joystick. Thanks for hanging out, Chris. You know, if you're not in the right shot, you're a little bit to the left production. You can just move you.

Starting point is 03:01:40 That's actually, I love that. You will have one or two customers for this. Autonomous chair, I love it. Autonomous office chair. Hey, you have to leave the meeting. Go back to your desk. Drive you around it. I think we're on to something.

Starting point is 03:01:54 Well, thank you so much for taking the time. Great to meet, Chris. Yeah, thanks for having. That's on the show. Thank you. Thank you. We'll talk to you soon. Goodbye. Let me tell you about app loving. Profitable advertising made easy with axon.a.combe, get access to over one billion billion daily active users and grow your business today. What's up?

Starting point is 03:02:11 Brett Adcock. It was on the show yesterday. He had some interesting comments about the state of AI. Okay. I disagreed strongly with many of them. Okay. But we have to cover this video from the Sean Ryan podcast. Yes. It's a new gate. Okay. It's a new gate. It's, they're calling it telegate adgate ad well maybe that too who knows so so he is hanging out with a figure robot okay uh on the sean ryan podcast oh okay he went outside for it yeah i was wondering because like sean ryan normally shoots not like very cinematic whiskey bar uh but he's outside and there's like a two-minute video where they're hanging out with the robot yes let's pull this up and i want to get your take all right turn around so this is the first time it tells us that's fine it tells us that's

Starting point is 03:02:59 another thing too is like we basically the robot's But at the end of the video, it starts turning around and then he says turn around. And Nima here says the video is the smoking gun that figures robots are teleopt. Again, I love teleop, not a problem. But Brett has insistently said He's not doing teleop.

Starting point is 03:03:19 He never do teleop. He says not autonomous. Notice how the robot starts turning around before Brett says, all right, turn around. Yeah, you can skip forward a little bit. And there's pull up, pull up this other video that I'm actually on. There's another, yeah, there's another video quoting this that shows it on repeat.

Starting point is 03:03:37 Let's see. Now, one thing too is like we basically, the robots almost all a fully soft wrap. It's by Vic, Vick, quote, and said, yeah, okay, yeah, it's definitely not waiting for the command. Okay, so it's very, this one. All right, it's very subtle,

Starting point is 03:03:51 but you can see it's turning around, and then he says, all right, turn around. Yes, but the steel man here? Premonition. All, turn around. about knew what was going to happen because personalized super intelligence understands that a turnaround command is coming before Brett even says it starts turning around before. So that would be one possible solution. But yes. Who knows? Also, the moment from yesterday that stands out to me is I said,

Starting point is 03:04:17 why build a separate AI lab focused on personal superintelligence outside of your company that is trying to sell some combination of intelligence in the physical world. And he said, I really value focus, which I thought was fascinating given that he is diverting his personal focus. His personal focus. Yeah, it's like focus within an organization, like a specific, like the leaders that joined that company can focus just on that problem. It was, it was an odd comment to sort of process. Yes, the, I mean, I don't know. I haven't watched the full interview with Sean Ryan. I wonder if he talks about whether or not this particular robot is teleop, because it's totally reasonable that a company would have some teleop robots, some autonomous robots, and sort of mix and match them based on the particular demo. Obviously, if you're doing some sort of prescripted stunt dance or parkour scenario, you might prescript that. And then ideally you would say, hey, you know, this one's teleop. Here's a demo of what we're capable of when we're using teleop. Here's a demo of what we're capable of when we're fully autonomous,

Starting point is 03:05:32 when we're partially remote controlled or something like that, somewhere in between. I don't know. We'll see. You know, people will continue to dig in. I mean, all of this, you know, the rubber meets the road when the robots are out in the wild. When people get them and they start shipping and people can see, unless you buy one and it's secretly teleop, that would be wild. You're like, wow, this is remarkable.

Starting point is 03:05:55 I can give it the most complex, I can give it the most complex vague instructions. It just does exactly what I do. If the figure robot can simply open a Diet Coke for John, we're a buyer. That's the goal. We don't need it to do everything. That's the goalpost. We just need it to do one thing really well. A six pack of Diet Coke.

Starting point is 03:06:14 Tyler, what do you think about the figure gate? I mean, it's hard to say just from that video, but I think broadly like, people are probably like two against teleoperation generally. I agree. Because, like, you know, the lesson from Waymo is that, like, actually... It's goaded. You know, part... Maybe if it's totally, like, 100% teleop, like, okay, that's not great.

Starting point is 03:06:34 But if it's, like, partly, like, there's someone overseeing it. Yeah. And maybe they're, like, pretty involved sometimes. It can be, like, extremely valuable. Like, Waymo is a great product, whatever. Yeah. Like, even just, like, deploying robots in dangerous locations, if it's fully teleopt, that's still, like, a great thing.

Starting point is 03:06:49 And, like, clearly, the way we get fully autonomous robots is by starting out with partially telop one. get the data. There's like a very clear loop there. So I think broadly people are too against. I completely agree. Yeah. Anyway, anything else we need to talk about? No. We talked about we'll be back tomorrow. Oh, we do have we do have one follow up to yesterday. So we did a little deep dive from the Wall Street Journal on Mark Lanier, the lawyer who successfully argued that meta and YouTube are addictive in the LA court last week. And we posted the clip. A lot of people enjoyed learning about him. And in particular,

Starting point is 03:07:25 the fact that he has a menagerie that contains lemurs and llamas, as well as a 120-person train. We love the way he's living his life. We're huge fans of Mark Lanier, although do have some disagreement around the legal findings. But a lot of people chimed in. Excel Rader said, by the way, this is the Lanier Theological Library in Houston, which is open to the public for touring. Incredible guy. Shares two amazing images of, you know, what an amazing

Starting point is 03:07:55 contribution to the community. And Eric Suford, quote, tweeted our post and said, this is true. I grew up down the street from his property, and he hosted a high school graduation party for one of my friends. He recently bought an adjoining horse ranch and built a seminary on it. So a lot of people coming out in support of Mark Lanier. And yeah, I mean, just seems like, seems like a fantastic lifestyle. We'll get him on the show. Fantastic menagerie. And he really reset, you know, everyone's, everyone focuses on, oh, are you flying private? Are you post-economic? Like menagerie is clearly just a different tier, different ladder. That's where you want to go in life if you're successful. And he's done it. So,

Starting point is 03:08:35 congrats to him. Anyway, thank you so much for tuning in to TBPN today. Leave us five stars on Apple podcast and Spotify. Sign up for a newsletter at tbpn.com. A wonderful last few hours of your quarter. Yes. It's been an honor. See you tomorrow. Goodbye.

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